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Mask R-CNN is an instance segmentation model that allows us to identify pixel wise location for our class. “Instance segmentation” means segmenting individual objects within a scene, regardless of whether they are of the same type — i.e, identifying individual cars, persons, etc. Check out the below GIF of a Mask-RCNN model trained on the COCO dataset. As you can see, we can identify pixel locations for cars, persons, fruits, etc.

Mask R-CNN is different from classical object detection models like Faster R-CNN where, in addition to identifying the class and its bounding box location, it can also color pixels in the bounding box that correspond to that class. When do you think we would be need this additional detail? Some examples I can think of are:

Self-Driving Cars need to know the exact pixel location of the road; potentially of other cars as well to avoid collisions

Robots may need pixel location of objects that they want to pick up (Amazon’s drones comes to mind here)

The easiest way to try a Mask R-CNN model built on COCO classes is to use the Tensorflow Object Detection API. You can refer to this article (written by me) that has information on how to use the API and run the model on YouTube videos.

How Mask R-CNN works

Before we build a Mask R-CNN model, let’s first understand how it actually works.

A good way to think about Mask R-CNN is that it is a combination of a Faster R-CNN that does object detection (class + bounding box) and FCN (Fully Convolutional Network) that does pixel wise boundary. See figure below:

                                                                         Mask RCNN is a combination of Faster RCNN and FCN

Mask R-CNN is conceptually simple: Faster R-CNN has two outputs for each candidate object, a class label and a bounding-box offset; to this we add a third branch that outputs the object mask — which is a binary mask that indicates the pixels where the object is in the bounding box. But the additional mask output is distinct from the class and box outputs, requiring extraction of much finer spatial layout of an object. To do this Mask R-CNN uses the Fully Convolution Network (FCN) described below.

FCN is a popular algorithm for doing semantic segmentation. This model uses various blocks of convolution and max pool layers to first decompress an image to 1/32th of its original size. It then makes a class prediction at this level of granularity. Finally it uses up sampling and deconvolution layers to resize the image to its original dimensions.

So, in short, we can say that Mask R-CNN combines the two networks — Faster R-CNN and FCN in one mega architecture. The loss function for the model is the total loss in doing classification, generating bounding box and generating the mask.

Mask RCNN has a couple of additional improvements that make it much more accurate than FCN. You can read more about them in their paper.

How to build a Mask R-CNN Model for Car Damage Detection

For building a custom Mask R-CNN, we will leverage the Matterport Github repository. The latest TensorFlow Object Detection repository also provides the option to build Mask R-CNN. However I would only recommend this for the strong-hearted! The versions of TensorFlow, object detection, format for mask, etc. can demand debugging of errors. I was able to successfully train a Mask R-CNN using it.

But I have seen many people struggle with all kinds of errors. So I now highly recommend the Matterport Mask R-CNN repository to anyone venturing into this domain.

Collecting Data

For this exercise, I collected 66 images (50 train and 16 validation) of damaged cars from Google. Check out some examples below.

Annotating the Data

A Mask R-CNN model requires the user to annotate the images and identify the region of damage. The annotation tool I used is the VGG Image Annotator — v 1.0.6. You can use the html version available at this link. Using this tool you can create a polygon mask as shown below:

Once you have created all the annotations, you can download the annotation and save it in a json format. You can look at my images and annotations on my repository here.

Training a model

Next we will load our images and annotations.

class CustomDataset(utils.Dataset): def load_custom(self, dataset_dir, subset): """Load a subset of the Balloon dataset. dataset_dir: Root directory of the dataset. subset: Subset to load: train or val """ # Add classes. We have only one class to add. self.add_class("damage", 1, "damage") # Train or validation dataset? assert subset in ["train", "val"] dataset_dir = os.path.join(dataset_dir, subset) # We mostly care about the x and y coordinates of each region annotations1 = json.load(open(os.path.join(dataset_dir, "via_region_data.json"))) annotations = list(annotations1.values()) # don't need the dict keys # The VIA tool saves images in the JSON even if they don't have any # annotations. Skip unannotated images. annotations = [a for a in annotations if a['regions']] # Add images for a in annotations: # Get the x, y coordinaets of points of the polygons that make up # the outline of each object instance. There are stores in the # shape_attributes (see json format above) polygons = [r['shape_attributes'] for r in a['regions'].values()] # load_mask() needs the image size to convert polygons to masks. image_path = os.path.join(dataset_dir, a['filename']) image = height, width = image.shape[:2] self.add_image( "damage", ## for a single class just add the name here image_id=a['filename'], # use file name as a unique image id path=image_path, width=width, height=height, polygons=polygons)

Further, you can use this notebook to visualize the mask on the given images. See an example of this below:

To train the model, we use the COCO trained model as the checkpoint to perform transfer learning. You can download this model from the Matterport repository as well.

To train the model, run the below code block:

## Train a new model starting from pre-trained COCO weights python3 chúng tôi train --dataset=/path/to/datasetfolder --weights=coco ## Resume training a model that you had trained earlier python3 chúng tôi train --dataset=/path/to/datasetfolder --weights=last

I am using a GPU and trained the model for 10 epochs in 20–30 minutes.

Validate your model

You can inspect the model weights using the notebook — Inspect Custom Weights. Please link your last checkpoint in this notebook. This notebook can help you perform a sanity check if your weights and biases are properly distributed. See a sample output below:

Run model on images and make predictions

Use the notebook inspect_custom_model to run model on images from test/val set and see model predictions. See a sample result below:

And there you have it! You just built a Mask R-CNN model to detect damage on a car. What an awesome way to learn deep learning.

End Notes

Mask-RCNN is the next evolution of object detection models which allow detection with better precision. A big thanks to Matterport for making their repository public and allowing us to leverage it to build custom models. This is just a small example of what we can accomplish with this wonderful model.

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The Ultimate Guide To Creating A True ‘Ultimate Guide’

From choosing the right keywords, to conducting audience research, to writing engaging titles, it can be a long, painstaking process to create content that outranks your top-ranking competitors.

This desire to create bigger and better content has led to this often cringe-worthy trend: turning every article into an “ultimate guide”.

Is There Such a Thing as an ‘Ultimate’ Guide?

“Ultimate guide” implies that your content is the best, right? That no one else can top it. That it’s the blog post to end all blog posts.

The issue is that with so many articles claiming to be “ultimate guides”, throwing this into your post title has started to lose its meaning. Claiming that your article is the best doesn’t make it so.

It’s in the value.

Here’s how to create a true ultimate guide – the right way – in order to attract more organic traffic and get readers raving about your content.

An Ultimate Guide Is More Than Just a Listicle

Many content creators and SEO professionals approach content with the belief that longer is better – despite the numerous studies that have shown diminishing returns on content that is too long.

There’s a sweet spot for every topic and niche, and simply adding more bullet points for “top tips” to your ultimate guide does not necessarily mean you are adding more value.

Your goal in creating an ultimate guide is to provide better information than all of the top-ranking posts for your chosen focus keyword.

You do that not by making it longer (necessarily), but by doing your research to determine what the existing articles offer that your guide has to have.

Step 1: Have a Purpose (Beyond Ranking)

I get it. It’s enticing to go after those sweet money keywords when you see an opportunity to outrank your competitors.

But beyond rankings, there’s typically the ultimate goal of getting readers to take action – by subscribing, by buying a project, or by filling out a form.

That’s why it’s short-sighted to create an ultimate guide for the sole purpose of targeting a particular keyword. Instead, it’s best to have a strategy that works to drive conversions through your content.

Before writing your ultimate guide, consider what action (if any) you want readers to take. Are you:

Simply aiming to inform readers about a topic?

Trying to build brand trust?

It’s essential that you know your end goal.

Having a clear objective in mind will help you determine what value you need to provide and how. It will keep you focused on writing content that serves to not only attract traffic but also make the most of that traffic.

Step 2: Choose Your Keyword(s)

Not every keyword is suited for an ultimate guide.

Just because your goal is to provide more value than the content that’s already ranking, doesn’t mean throwing “ultimate guide” in front of it is the move. It may be better suited for a different type of content (like a standard blog post or a listicle).

“Ultimate guide”-type keywords are ones that warrant a well-thought-out, in-depth piece of content. They should be topics that necessarily require a comprehensive guide in order to leave readers feeling sufficiently informed.

Relatively broad topics are a great fit an ultimate guide because they require many sections, explanations, examples, and actionable steps.

“Best places to visit in Thailand” can be summed up in a relatively concise listicle. “How to travel in Thailand” leaves much more room for elaboration.

Consider whether an ultimate guide would do your chosen keyword justice, or whether a different type of content would be a better fit instead. Some things to consider are:

What is the user intent behind the keyword?

Could you answer the user’s primary question in a relatively short (or standard-sized) article?

Can you effectively write a comprehensive guide about the topic without stuffing it full of fluff?

Are there already tons of “ultimate guides” about this topic?

Are you confident that you can at least offer 2X the value of the top-ranking articles?

In summary, choose keywords that warrant a comprehensive piece of content.

If you feel that in order to create an ultimate guide you’ll have to chock your content full of useless facts and tips, you should probably take a different approach.

Step 3: Scope out the Not-So-Ultimate Guides

Not all ultimate guides are created equal.

If you’ve decided that your focus keyword warrants an ultimate guide, then your next step should be to look at what’s already ranking. Chances are, you’ll find some existing “ultimate guides”.

In this step, you’ll want to look at what your competitors are doing right and wrong.

Are they simply regurgitating the same-old information?

Are they bringing anything unique to the table?

How can you learn from them and make your content 2X better?

Since your competitors are ranking for that keyword, they must be doing something right.

Look for similarities and characteristics that you think may be giving them a competitive edge. Then, looks for gaps in information that you can fill with your ultimate guide.

Your ultimate guide – as the name implies – should aim to be the best of the best. That means capitalizing off of what your competitors are doing right and then making your content even better.

Step 4: Survey Your Audience

Want to know what your audience really wants to read? Ask them!

The best way to provide the most value in your ultimate guide is to ask your readers what they are interested in.

You can survey your audience casually (by asking them questions on social media) or by sending them an official survey (directly or via email). Their answers will help you determine what information to include in your guide.

Here are some questions you can ask your audience:

What is your top struggle when it comes to dealing with [ topics/problem ]?

What are three questions you have about [ topic ]?

What do you wish other brands knew about [ topic ]?

What are some solutions you have tried to solve [ problem ]?

What’s your top tip when it comes to [ topic ]?

In SEO content, it’s best to avoid making guesses when you can get your answers straight from the source.

By asking your audience directly, you can be sure to write content that answers their most burning questions, thoroughly covers the topic, and provides the value that your particular audience is looking for.

Step 5: Include Case Studies, Examples & Statistics

Any claims that you make in your ultimate guide should be supported by case studies, examples, or statistics.

Including this information serves to provide value to your readers in a variety of ways:


Including sources shows your readers that you know what you are talking about.

In other words, it helps establish you as an authority on the topic.

Rather than making baseless claims, you can back up all of your information with facts.


Referencing sources helps build trust with your audience.

When people are confident that the information you are providing is accurate, they are more likely to buy from you.


Including examples helps readers make the connection between the information in your ultimate guide and how they can apply it to their lives or businesses.

Examples prove that the tips or strategies you are sharing work and that by taking action readers can see similar results.


“E-A-T” is a principle in SEO that stands for Expertise, Authoritativeness, and Trustworthiness.

Google’s Danny Sullivan has suggested that the secret to better rankings is better content. And the key to better content? You can find that in the quality raters guidelines, which talks in great detail about E-A-T.

By including case studies, examples, and sources in your ultimate guide, you’ll indicate to search engines that your content is valuable, accurate, and comes from a reputable source.

Following this step is another way to provide value where your competitors may be coming up short.

Step 6: Make It Actionable

If you know the search intent behind the keyword you are targeting with your ultimate guide, then you should be able to make a guess about what users are trying to achieve by reading your content.

Most times, their goal is to get their most pressing questions answered. Why? Because they are likely experiencing an issue that needs fixing, or want to learn more about a topic.

Your best bet in creating your ultimate guide, then, is to make the information you provide actionable in some way. You want to do your very best to help them fix whatever problem they are experiencing and answer every question they may have.

If your ultimate guide is about “how to plan a honeymoon”, you’ll likely want to include tips like:

Where and how to hire a travel planner.

How to choose the best hotel.

How to prepare for international travel.

How to budget for a honeymoon.

Best places to book affordable airfare.

Even better, these actionable steps all provide an opportunity for you to link to other related content on your site. Either way, you are giving the readers the information they need to apply your tips to their lives.

Not only will making it actionable put your guide miles above competing articles, but it’ll make it more likely that your guide will drive conversions.

If you are able to offer all of the information they need on your site, it’ll be easy to direct them to your products and done-for-you services.

Step 7: Make It Pretty

Creating an ultimate guide takes time – and, often, money. To truly make an “ultimate” guide, you won’t want to cut corners.

Make the most of the work and resources you are putting in by making your guide attractive and eye-catching, as well as informative. It’ll be worth it to employ a graphic designer and/or web developer to create a sleek, on-brand looking guide.

Including various types of media – like videos, infographics, and images – will also help you repurpose your content across multiple platforms. You can build out an entire content marketing strategy from a single piece of content.

Step 8: Add a Content Upgrade

Assuming your content is optimized to the nines and starts generating organic traffic, you’ll also want to be sure you are making the most of that traffic.

Beyond including links to your product pages or adding calls-to-action, you can incorporate a content upgrade to get readers to join your email list.

Content upgrades work great because they entice readers with even more valuable content than what you are already offering in your ultimate guide. If the upgrade is irresistible, users will hand over their email addresses in exchange for more juicy content.

Some possible content upgrade ideas include:

A free downloadable ebook.

A link to an exclusive expert interview.

A free sign-up for a 5-day email course.

A discount code for a paid product.

An expanded ultimate guide (e.g. “Get the rest of the tips here!”).

A free design or strategy template.

By adding a content upgrade to your ultimate guide, you can capture some of that traffic coming in and remarket to them later.

You’re essentially giving users multiple ways to opt-in (convert) – ensuring that you are making the absolute most of the traffic your content is generating.

Examples of Ultimate Guides That Get It Right

If you want to create the ultimate “ultimate guide”, it’s recommended that you learn from those that are already doing it right.

After following the tips above, look to some of these examples to find ways to make your guide even better.

Create Your Ultimate ‘Ultimate Guide’

Think you have what it takes to create a true “ultimate guide”?

Remember that your primary objective is to provide even more value than what’s already ranking.

Simply calling your guide an “ultimate guide” isn’t enough.

Follow the steps above in order to target the best keyword, create content your audience truly wants to read and provide accurate, actionable information that grabs users’ (and Google’s) attention.

More Resources:

Image Credits

Streamlit Vs Gradio – A Guide To Building Dashboards In Python


Machine Learning is a fast-growing field, and its applications have become ubiquitous in our day-to-day lives. As the demand for ML models increases, so makes the demand for user-friendly interfaces to interact with these models. This blog is a tutorial for building intuitive frontend interfaces for Machine Learning models using two popular open-source libraries – Streamlit vs. Gradio.

Streamlit is a python library for building data-driven applications specifically designed for machine learning and data science. It makes it easy to create a frontend UI in just a short amount of time with multiple features. On the other hand, Gradio is a library for Machine Learning models that makes it possible to quickly and easily create web-based interfaces for your models.

Together, these two libraries provide a powerful solution for building interfaces for Machine Learning that are both functional and user-friendly. In this blog, we will see how to build interactive interfaces using Streamlit and Gradio and how they can improve user experience when interacting with ML models. For both beginners and experienced data scientists, this blog will provide you with the tools you need to create your interfaces. So, in this article, we will discuss Streamlit vs. Gradio.

This article was published as a part of the Data Science Blogathon.

Table of Contents Streamlit Architecture

Streamlit is a modern, easy-to-use, open-source python library that allows developers to build beautiful and interactive data applications. With Streamlit, you can easily create beautiful visualizations and interactive dashboards. Streamlit is built using the Python programming language, making it handy for data scientists and machine learning engineers already familiar with Python. However, even if you’re unfamiliar with Python, Streamlit is designed to be easy to learn and use, with a simple and intuitive API that makes it easy to get started. This is about Streamlit now. Further, we will see Streamlit vs. Gradio.

Streamlit works by using Flask to provide a server-side environment for Python code and React to provide a client-side environment for rendering and interacting with the results of that code.

When a Streamlit application is run, the Flask server is started and listens for API calls from the user’s browser. When a user interacts with the application, the React front-end sends an API call to the Flask server, executing the appropriate Python code and returning the results to the user’s browser, where they are rendered and displayed.

Installation and Imports

Let’s start by installing and importing streamlit and other libraries necessary for this tutorial. We will use scikit-learn’s logistic regression model for this tutorial.

!pip install streamlit #Import Streamlit import streamlit as st #Other imports import pandas as pd import numpy as np from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression import matplotlib.pyplot as plt from sklearn.metrics import accuracy_score from sklearn.preprocessing import StandardScaler Creating the Dashboard

We will create the dashboard for model training. Here’s an example of how you can create a dashboard using streamlit to train a scikit-learn model, with the option to upload the input data:

# Title of the dashboard st.title("Streamlit Dashboard for Model Training") #User uploading feature for input csv file st.write("Upload your dataset (CSV file format)") file = st.file_uploader("", type="csv") #read the csv file and display the dataframe if file is not None: data = pd.read_csv(file) st.write("Preview of the uploaded dataset:") st.dataframe(data) target = st.selectbox('Select the target variable: ', list(data.columns), index = list(data.columns).index(list(data.columns)[-1])) X = data.drop(columns=target) y = data[target] # split the dataset into train and test and traina logistic regrresison model st.write("Splitting the dataset into training and testing sets:") X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0) sc = StandardScaler() X_train = sc.fit_transform(X_train) X_test = sc.transform(X_test) st.write("Training a Logistic Regression Model:") model = LogisticRegression(random_state = 0, solver='lbfgs', multi_class='auto'), y_train) #Evaluate the model and print the accuracy score st.write("Evaluating the Model:") y_pred = model.predict(X_test) accuracy = accuracy_score(y_test, y_pred) st.write("Accuracy: ", accuracy) st.write("End of Training")

In this example, we use a file uploader to let the user choose between different pages. Depending on the uploaded file, we display the Dataframe of the uploaded file and let the user choose the target variable column. The code then standardizes the data, trains a logistic regression model, and prints the accuracy.

Let’s try it with the iris dataset, which can be downloaded from several sources. Below is a screenshot of the dashboard:

Multiple Pages in Streamlit

Streamlit supports creating multiple pages for the app, which can be added with a few lines of code as below:

menu = ["Homepage", "Page 1", "Page 2"] choice = st.sidebar.selectbox("Select a page", menu) if choice == "Homepage": st.write("Welcome to the Homepage!") elif choice == "Page 1": st.write("This is Page 1") elif choice == "Page 2": st.write("This is Page 2")

This can have several pages for model training, predictions, and visualizations.  The user can choose the page from the sidebar, displaying the appropriate menu and options.


Streamlit provides several built-in functions for creating different types of visualizations, including:

st.line_chart: For line charts

st.area_chart: For area charts

st.bar_chart: For bar charts

st.write with a pandas dataframe: For tables

st.write with a Matplotlib plot: For custom plots

st.write with a Plotly figure: For interactive plots

Here’s a simple example that shows how you can create a histogram in Streamlit:

nums_data = np.random.normal(1, 1, size=100) fig, ax = plt.subplots() ax.hist(nums_data, bins=20) st.pyplot(fig)

This creates the following histogram:

Now let’s look at Gradio and build a new dashboard to compare the libraries.

Gradio Architecture

Gradio is an open-source library that provides tools for building and deploying interactive interfaces for machine learning models. It allows you to easily turn your machine-learning models into web-based applications that can be used by all users, including those with little to no coding experience. With Gradio, you can create interactive sliders, dropdown menus, and checkboxes to control the inputs to your model and display the outputs using visualizations for charts, tables, and images. It can be integrated with Pytorch and TensorFlow for deep learning, making it easy to use your existing models or train new ones. This is about Gradio now. Further, we will see Streamlit vs. Gradio.

One of the key features of the Gradio library is its modular architecture. This allows developers to easily add or remove components and functionality as needed, creating a wide range of interfaces.

Let’s look at the process of creating a dashboard with Gradio:

Installation and Imports

Let’s start by installing and importing Gradio and other necessary libraries.

#Install Gradio !pip install gradio import gradio as gr #Other Imports import os import pandas as pd import numpy as np from sklearn.linear_model import LogisticRegression from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score Creating the Dashboard

We will build the dashboard with similar features as we did with Streamlit and let the user choose the input file. The data frame will be displayed on the right, and the model training will happen in the background. Let’s start by defining the model training steps:

# Train the model def train_model(data, target): # dependent and independent variables X = data.drop(columns=target) y = data[target] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0) #standardize the data sc = StandardScaler() X_train = sc.fit_transform(X_train) X_test = sc.transform(X_test) #train the model model = LogisticRegression(random_state=0, solver='lbfgs', multi_class='auto'), y_train) #print the accuracy score y_pred = model.predict(X_test) accuracy = accuracy_score(y_test, y_pred) return accuracy

The user will be given the option to upload or select the file location. In this case, let’s try a dropdown where the user selects a CSV file, with the list of options showing all CSV files in the current working directory.

# Upload csv file and train the model def upload_csv(Input_CSV, Target_Variable): columns = list(pd.read_csv('./' + Input_CSV).columns) if Target_Variable not in columns: Target_Variable = columns[-1] data = pd.read_csv('./' + Input_CSV) accuracy = train_model(data, Target_Variable) return (data.head(4)), Target_Variable, accuracy #list the csv files in current working directory files = [f for f in os.listdir('.') if os.path.isfile(f) and f.endswith('csv')] #set the inputs and corresponding outputs inputs = [gr.Dropdown(files), gr.Textbox()] outputs = ['dataframe', gr.Textbox(label="Target Variable"), gr.Textbox(label="Accuracy Score")] #launch the dashboard demo = gr.Interface(upload_csv, inputs, outputs) demo.launch() #in some cases this line might produce an error # in case the above block of code throws error # an argument needs to be passed in launch() # demo.launch(share=True) # the above line when run, solves the error

The dashboard is launched locally, and from the view in the browser, we can select the CSV file, train a logistic regression model, and it outputs the accuracy score.

We compare the two dashboards and the process of building them – Streamlit, with its well-documented modules and support for various popular machine learning libraries, including TensorFlow, Keras, and PyTorch, makes it easy to build the interface quickly. On the other hand, Gradio is useful for simple and easy-to-use interfaces with a list of inputs on the left, the function executing in the background on these inputs, and the outputs displayed on the right.


The dashboards built using Gradio and Streamlit are user-friendly and efficient tools for training any ML models and displaying the visualizations, outputs, graphs, and metrics. Streamlit provides a larger support base and detailed documentation and examples, whereas Gradio is for quick visualization of inputs and outputs side by side. Both libraries provide easy-to-use, quick dashboard-building modules that are user-friendly, fast, and efficient, and the choice is left to the end user to decide the better library based on their use case.

The Key takeaways of the article are as follows:

Streamlit is designed to be easy to use, with a simple syntax for creating UI elements, importing data, and creating charts and plots.

Streamlit is well-documented and has a large user base with good community support.

Gradio focuses on providing a simple and intuitive interface for users to input values and receive predictions from machine learning models.

Streamlit allows for more user interface customization and flexibility in the application’s design. Gradio, on the other hand, has more limited customization options and is geared more toward creating functional interfaces for deep learning models.

Gradio provides a quicker development environment compared to Streamlit. This allows developers to prototype their ideas and get to build faster quickly.

So, this article definitely provides you the knowledge about Streamlit vs. Gradio.

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The Ultimate Guide To Smartphone Productivity Apps

There are a wide variety of productivity apps available, so you can find one that fits your specific needs. Whether you’re looking for a to-do list app, a time tracking app, or a focus blocker, there’s an app out there that can help you boost your productivity.

The Benefits of Using Smartphone Productivity Apps

Smartphone productivity apps can be a great way to boost your productivity in 2023. These apps can help you stay organized, track your time, and focus on tasks. They can also help you collaborate with others and get more done.

There are many different types of smartphone productivity apps available, so you can find one that fits your needs. Some popular options include to-do list apps, time tracking apps, focus blockers, note-taking apps, and project management apps.

To get the most out of smartphone productivity apps, it is important to use them consistently. Make sure to set clear goals and priorities, and use the apps every day. You may also want to experiment with different apps and settings until you find what works best for you.

Here are a few of the best smartphone productivity apps in 2023:

Boost Your Productivity in 2023 with Smartphone Productivity Apps

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To-do list apps

Todoist: Todoist is a popular to-do list app that allows you to create tasks, set due dates, and add subtasks. You can also prioritize your tasks and set reminders. Todoist is available for free, but there is also a paid premium plan that offers additional features.

TickTick: TickTick is another popular to-do list app that offers a variety of features, including task automation, a pomodoro timer, and a focus mode. TickTick is available for free, but there is also a paid premium plan that offers additional features.

TickTick app logo

Google Tasks: Google Tasks is a simple to-do list app that is integrated with Google Calendar and Gmail. This makes it easy to add tasks to your calendar or send yourself reminders. Google Tasks is free to use.

Time tracking apps

RescueTime: RescueTime is a time tracking app that helps you see how you’re spending your time. This information can help you identify areas where you can be more productive. RescueTime is available for free, but there is also a paid premium plan that offers additional features.

Toggl: Toggl is another popular time tracking app that offers a variety of features, including task management, reports, and integrations with other apps. Toggl is available for free, but there is also a paid premium plan that offers additional features.

Hours: Hours is a simple time tracking app that is easy to use. It tracks your time automatically, so you don’t have to remember to start and stop the timer. Hours is free to use.

Focus blockers

Forest: Forest is a focus blocker app that uses gamification to help you stay focused. When you start a session, a tree will start to grow. If you leave the app, the tree will die. Forest is a great way to avoid distractions and get more done.

FocusList: FocusList is another focus blocker app that offers a variety of features, including a timer, a pomodoro timer, and a distraction-free mode. FocusList is available for free, but there is also a paid premium plan that offers additional features.

Freedom: Freedom is a powerful focus blocker app that allows you to block specific websites, apps, and even entire categories of websites. Freedom is a great way to eliminate distractions and get more done.

These are just a few of the many productivity apps available for smartphones. With so many options to choose from, you’re sure to find one that fits your needs and helps you boost your productivity in 2023.

Here are some additional tips for using smartphone productivity apps effectively:

Set clear goals and priorities. Before you start using any productivity app, take some time to think about what you want to achieve. What are your goals for the day, week, or month? Once you know what you want to achieve, you can start to create tasks and set priorities.

Use the right app for the job. There are many different productivity apps available, so it’s important to choose the right one for the task at hand. If you’re trying to stay organized, a to-do list app might be the best choice. If you’re trying to focus on a task, a focus blocker app might be a better option.

Be consistent. The key to using productivity apps effectively is to be consistent. Use the apps every day and make them a part of your routine. The more you use them, the more effective they will be.

Don’t be afraid to experiment. There are many different productivity apps available, so don’t be afraid to experiment and find the ones that work best for you. Try out different apps and see

Don’t be afraid to experiment. There are many different productivity apps available, so don’t be afraid to experiment and find the ones that work best for you. Try out different apps and see what features you like and dislike. You may find that you prefer a combination of different apps to meet your needs.

Set up your phone for productivity

In addition to using productivity apps, you can also set up your phone for productivity. Here are a few tips:

Turn off notifications. Notifications can be a major distraction, so turn them off for apps that you don’t need to be notified about.

Rearrange your home screen. Put your productivity apps front and center on your home screen so that you can easily access them.

Use a password manager. A password manager can help you keep track of all of your passwords and keep them secure.

Track your phone usage. There are apps that can help you track how you’re using your phone. This information can help you identify areas where you can be more productive.

Here are some additional smartphone productivity apps that you may want to consider:

Evernote: Evernote is a note-taking app that allows you to create notes, organize them, and access them from anywhere.

Google Keep: Google Keep is a simple note-taking app that is integrated with other Google products.

Notion: Notion is a powerful productivity app that allows you to create documents, databases, and more.

Trello: Trello is a Kanban-style productivity app that allows you to organize your tasks and projects.

Slack: Slack is a team communication app that allows you to chat, share files, and collaborate with others.

With so many great options available, there’s sure to be a smartphone productivity app that can help you boost your productivity in 2023.

Here are some additional things to consider when choosing and using smartphone productivity apps:

Your individual needs: What are your specific productivity goals? Do you need help staying organized, tracking your time, or focusing on tasks? Once you know what you need, you can start to narrow down your choices.

The features you want: Not all productivity apps are created equal. Some offer a wide range of features, while others are more basic. Make sure to choose an app that has the features you need to be productive.

The user interface: The user interface (UI) is the way that an app looks and feels. It’s important to choose an app with a UI that you find easy to use and navigate.

The price: Productivity apps can range in price from free to $100 or more. Choose an app that fits your budget.

Once you’ve chosen the right productivity apps for you, it’s important to use them effectively. Here are a few tips:

Use the apps every day: The key to using productivity apps effectively is to be consistent. Use the apps every day and make them a part of your routine. The more you use them, the more effective they will be.

Be flexible: Don’t be afraid to change your approach if you’re not seeing results. Experiment with different apps and settings until you find what works best for you.

Take breaks: It’s important to take breaks when you’re using productivity apps. Get up and move around, or take a few minutes to relax and clear your head. This will help you stay focused and productive.

By following these tips, you can use smartphone productivity apps to boost your productivity in 2023. So what are you waiting for? Start using these apps today and see how much more you can get done.

The Ultimate Guide To Proper Pc Cable Management

There’s no doubt about it: Taking the time to tidy up your cables is something every system builder and upgrader should do.

Here’s how to transform that terrifying tangle of cables into a prim, polished PC.

Components matter

There is no secret to proper PC cable management. There are, however, a number of strategies to ensure a good outcome. It starts with wire ties, a keen eye, and a bit of patience, but the right components and component placement also matter greatly.

A little forethought can make a big difference to your case’s cable clutter.

Many cases, particularly higher-end models designed for enthusiasts, have numerous features designed to make internal cable management easier, including rubberized routing holes in the motherboard tray.

Many of today’s case manufacturers take cable management very seriously and have designed their products to tame tangles. They scatter strategically placed holes about the motherboard tray, leave adequate space behind the motherboard tray to hide and tuck cables away, and litter the case with tie-down spots.

When building a new system, we’d highly recommend buying such a case. It might cost a little more than a generic chassis, but it’s worth the investment and could last though multiple upgrade cycles.

Modular PSUs have their detractors, because technically speaking every connection or break in a wire increases its resistance. In the many years I’ve been building systems, however, I’ve never had a problem. Being able to use only the cables you need is great and eliminates the need to stash large, unused bundles of cable inside your case. Modular PSUs are not a necessity—in fact, the system featured at the end of this article doesn’t use one—but they will alleviate cable clutter.

Loyd Case

The raw components may look like a mess, but turning them into a neat, clean build doesn’t take much extra time at all.

When assembling a system I find it’s best to save the drives and power supply for last. When all of the other components are in place, it’s easier to see where to position the drive (or drives) and where to route cables.

Touch everything

Loyd Case

It’s best to snake the cables behind the motherboard tray and to not tie anything down until every cable has been connected and is roughly in the ideal position. I like to route and connect any front-panel or case-related cables first. Then I install any data cables for various drives, and finally place in the power supply. If you throw everything into the system willy-nilly and connect it all up, you’ll often find yourself disconnecting or moving things around to get the cabling right.

Keep airflow in mind; don’t cover any case fans or coolers with a cable if at all possible.

The vast majority of the cabling should wind up behind the motherboard tray in many builds. If your case doesn’t have cut-outs in the motherboard tray, try running all your cables along the side edge of the tray to achieve a clean look.

A behind-the-motherboard glimpse at a cleanly cabled system.

Velcro strips and twist ties are ideally suited to PC cable management, and adhesive tie downs can also come in handy if your case doesn’t already have tie down locations built-in. Heck, you can even use rubber bands! Don’t use zip ties if you can avoid it, however—if you ever need to remove a component or rewire your PC, zip ties have to be cut away, and it’s all too easy to slice a cable in the process. Stick to reusable, removable ties if at all possible.

Few cables can be seem from the front side of the same system. Success!

Now that you understand the building blocks of smart cable management, you may want to see smart cabling in action. Check out PCWorld’s guide to organizing your PC cables for a complete system build that discusses proper cable management each step of the way.

What about the outside?

A spiral wire wrap in action.

If you’re looking to tidy up the cables on the outside of your PC as well, all of the same suggestions apply. Disconnect all of the cables and reconnect them thinnest to fattest, giving each cable some individual attention. Connect any thin audio cables first, then move on to the USB cables, Ethernet cables, and power cables. Route each cable neatly, making sure not to create any tangles along the way, and then use Velcro strips to create tight bundles. Spiral wire wraps can also be great for tidying up the cables outside your PC.

How To Use Icloud Music Library – An Ultimate Guide

Apple wants you to have a seamless music experience irrespective of the device you use. Services like Apple Music and iTunes Match ensure that all your songs are available on your iOS device, Mac, and even PC or Android phone. The feature that makes all this possible is the iCloud Music Library. Here we’ve created the ultimate guide on how to use iCloud Music Library on iPhone, iPad, and Mac.

Note: iCloud Music Library, Sync Library, and Cloud Music Library are just different names for the same feature.

What is the iCloud Music Library?

Let us start with the basics. Suppose you have an iPhone, iPad, Mac, Windows PC, and an Android phone. You want your music on all these devices. Sure, you can connect the mobile devices to your computer and transfer the songs. You can do the same between two computers using an external drive.

But what if you wish to make this entire process effortless via the cloud. Well! iCloud Music Library (now shown as Sync Library) has got you covered.

Now you may ask how it does that!

How iCloud Music Library Works?

After you enable this option in the Music app or iTunes, it will first scan your existing songs. Next, using audio fingerprinting and metadata matching, it will see which of your songs are already available in the iTunes Store catalog. If a track is available, it won’t upload the file from your computer (to save time and space) but simply ‘match‘ the song and make it available on all your devices. This will be 256kbps AAC, DRM free! Sweet!

Pro Tip: Suppose you have a song named ‘I Like It’ in 128kpbs. If it matches in the iTunes Store catalog, you can download the track in 256kbps on your devices. This is an upgrade from the original lower quality!

In case you have songs (like local tracks or live versions of a song, etc.) that are not available in the iTunes Store, they will be uploaded from your Mac or PC in original form to Apple cloud servers and made available for streaming and downloading on all your other devices. Excellent!

The next natural question you may ask is, ‘How do I subscribe to this excellent feature?’

Sign into iCloud Music Library

With an Apple Music subscription ($9.99), you already get iCloud Music Library functionality.

However, if you use alternative music streaming apps like Spotify, you may not want to pay for Apple Music. In this case, you can subscribe to a service called iTunes Match ($24.99 per year). This will let you upload your existing songs from Mac or PC and make them available for streaming and downloading inside the Music app on iPhone, iPad, Android, etc.

Now that we are done with the basics, let us look at some essential bullet points that tell you more about iCloud Music Library.

You can have up to 100000 matched or uploaded songs. This does not count towards your iCloud storage.

Note that this 100000 songs limit does not include the music (songs or videos) you purchased via iTunes Store. Your purchased tracks are available on all devices without needing any subscription or special option like the iCloud Music Library.

If you have a song that does not match in the iTunes Store catalog and is of low quality (under 92kbps), it won’t be uploaded to iCloud. The same goes for a song over 200 MB in size, or more than two hours long, or purchased using someone else’s iTunes account.

You can stream and download songs in your iCloud Music Library on up to 10 devices.

Before You Begin:

Apple mentions that ‘after you turn on iCloud Music Library, all the music that’s currently on your iPhone and iPad is deleted and replaced with songs from iCloud.’ (But the Mac or PC you used to sync from previously still has the original files.)

Apple also makes it crystal clear that this is not a backup service. So before proceeding, make sure you take a backup of the music to an external drive.

Finally, you must know that since all music syncing will happen over the cloud, you won’t be able to transfer songs to iPhone using iTunes or the Finder.

How to Turn ON iCloud Music Library on Computer

To Enable iCloud Music Library on Mac

Note: On macOS Catalina and Big Sur, use the Music app. On macOS Mojave and earlier, use iTunes. The steps for both are almost identical.

To Enable iCloud Music Library on Windows

Depending on your library size and internet speed, it may take considerable time. You may see various cloud symbols next to the songs. A dotted iCloud icon mostly means the song is being uploaded.

If you have another computer, make sure to sign in to it using the same Apple ID and follow the exact above steps. This will ensure that your multiple libraries merge, and you have all songs from everywhere.

How to Turn ON iCloud Music Library on iPhone and iPad

After you enable cloud syncing on your Mac or PC, here’s how to do the same on your mobile devices.

Open the Settings app, scroll down, and tap on Music.

Turn on the toggle for Sync Library.

If you see a popup, read the description and choose ‘Keep Music’ or ‘Delete & Replace.’ In case you have previously synced songs from another computer, choose Keep Music. If you have just one music library, you may go with Delete & Replace. This will remove the current tracks from the iPhone and replace them with music in your iCloud Library.

If you have an unlimited mobile data plan, you may tap on Cellular Data and enable it on the next screen.

Once everything is set with iCloud Music Library, you can stream songs directly from the cloud or download it to save data and listen offline.

Open the Music app on your iPhone, iPad, or Android phone.

Tap on Library from the bottom row. Next, tap on Songs.

Tap on the song to play it.

Tap on the download icon to save it offline. In case you see no icon next to a song, this means it is already downloaded to the device.

To see only your downloaded songs, tap on Library → Downloaded.

In the same way, you can play or download songs on your Mac or PC using the Music app or iTunes.

Know the Status of Songs in iCloud Music Library

By following the steps below, you will get to know which of your songs are Matched, Uploaded, added from Apple Music, Purchased by you, Waiting to upload, Removed, Duplicate, or Ineligible for uploading.

Open the Music app or iTunes on Mac or PC.

How to Remove Songs from iCloud Music Library

On iPhone or iPad

Open the Music app on the iPhone or iPad.

Long-press on a song. Choose Delete from Library → Delete Song. (Or, if the song is downloaded, Remove → Delete from Library)

This will remove the song from all your iOS and iPadOS devices.

On Computer

Open the Music app or iTunes on Mac or PC.

What To Do If iCloud Music Library Does Not Work?

Here are some crucial points to consider if music isn’t syncing correctly among your devices.

In case you cancel your Apple Music or iTunes Match subscription, you will lose access to Cloud Music Library.

If you sign out of your Apple ID on any device, you won’t be able to use this feature.

Connect to a stable internet on your devices.

Double-check the above steps and make sure Sync Library is enabled on all the desired devices.

On mobile devices, keep the Music app open. Do not force close it. On the computer as well, make sure the Music app or iTunes is open.

In case an explicit song is grayed out, make sure to turn off Screen Time restrictions. If you are a child, you can not do this. And your guardian will most likely not turn it off for you!

Visit the Apple System Status page and ensure things like Apple Music, iCloud Account & Sign In, iTunes Match, iTunes Store have a green dot next to them.

Turn off Sync Library (steps below) and turn it back on after restarting your iPhone and Mac.

Deauthorize and re-authorize your computer.

In rare cases, it may be possible that the Apple Music song you added is no longer available due to licensing disagreements between the producer and Apple. Or, it might be available under a different name. Try searching for it again in Apple Music. Now, you can even search by lyrics!

Still, if you face problems, visit this page or contact Apple Support.

How to Disable iCloud Music Library on iPhone, iPad, or Mac

No longer wish to use this feature? Here’s how to turn off the iCloud Music Library on mobile devices and computers.

On iPhone and iPad: Open the Settings app → Music → turn off Sync Library → Turn Off. This will remove all Apple Music songs (added or downloaded) and all non-downloaded listings. However, this won’t remove those downloaded songs that were purchased, or matched, or uploaded.

What Happens If You Turn off the iCloud Music Library?

Your songs won’t be updated or made available wirelessly across devices.

Even if you have an Apple Music subscription, you will only be able to stream music and not add it to your library or download them offline.

After you turn off the iCloud Music Library, you can once again manually copy music from Mac or PC to iPhone or iPad via Lightning cable.

Signing Off


Author Profile


I have been an Apple user for over seven years now. At iGeeksBlog, I love creating how-tos and troubleshooting guides that help people do more with their iPhone, iPad, Mac, AirPods, and Apple Watch. In my free time, I like to watch stand up comedy videos, tech documentaries, news debates, and political speeches.

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