Learn how to Earn Money From GitHub?

GitHub really is an amazing web-based platform helping more than 60 million developers, programmers, or users shape their future in an open-source manner. And when it comes to making a business open-source, then it means a freemium model is there which can satisfy the hunger of many clients and tech-organizations located across the GLOBE just by sharing thoughts in terms of codes or writing solutions like blogs, articles, and guest posts. But have you ever thought that this freemium business model is comprised of ample opportunities which you can use as an earning machine in your side hustles with much confidence?

Ways to Earn money from GitHub

1. Monetize your GitHub Repository

2. Open Source Projects

3. Local Events

4. Find GitHub Repositories and Solve the Issues

5. Bug-Bounties


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Learn how to Earn Money From GitHub?
Raju Bhadra

Raju Bhadra


How to Earn PayPal Money as A Teenager for Free? ($20 to $30 Per Day)

Do you want to earn hassle-free PayPal money? It’s one of the easiest way to earn PayPal money online. Just simply upload images and earn PayPal money. In this tutorial, step-by-step I’ll show you everything. Anyone can do it. It’s open for all over the world.

Positive Sides of This Task:

1- You can make hassle-free PayPal money
2- You can earn $20 to $30 per day
2- Anyone can do it. (Worldwide Open)
3- Don’t need to use/buy any tools/software
4- Don’t need to make any content (Video or Website)
5- Don’t need to submit your credit card details
6- You don’t need any coding skills/marketing skills/working skills
7- Just spend less than 1 hour
8- 100% beginner-friendly

Negative Sides of This Task:

1- You can’t earn thousands dollars
2- If you use copy-right protected images then you get banned!

It’s one of the easiest way to earn PayPal money that I have ever seen. You don’t need to do any hard task for making PayPal money. If you serious about earning PayPal money then you can try it. As a teenager it’s the easiest way to earn PayPal money.

Watch Full Tutorial Here >>

#how to earn paypal money as a teenager #earn paypal money #how to earn paypal money

Edison  Stark

Edison Stark


How to Compare Multiple GitHub Projects with Our GitHub Stats tool

If you have project code hosted on GitHub, chances are you might be interested in checking some numbers and stats such as stars, commits and pull requests.

You might also want to compare some similar projects in terms of the above mentioned stats, for whatever reasons that interest you.

We have the right tool for you: the simple and easy-to-use little tool called GitHub Stats.

Let’s dive right in to what we can get out of it.

Getting started

This interactive tool is really easy to use. Follow the three steps below and you’ll get what you want in real-time:

1. Head to the GitHub repo of the tool

2. Enter as many projects as you need to check on

3. Hit the Update button beside each metric

In this article we are going to compare three most popular machine learning projects for you.

#github #tools #github-statistics-react #github-stats-tool #compare-github-projects #github-projects #software-development #programming

Jerad  Bailey

Jerad Bailey


Google Reveals "What is being Transferred” in Transfer Learning

Recently, researchers from Google proposed the solution of a very fundamental question in the machine learning community — What is being transferred in Transfer Learning? They explained various tools and analyses to address the fundamental question.

The ability to transfer the domain knowledge of one machine in which it is trained on to another where the data is usually scarce is one of the desired capabilities for machines. Researchers around the globe have been using transfer learning in various deep learning applications, including object detection, image classification, medical imaging tasks, among others.

#developers corner #learn transfer learning #machine learning #transfer learning #transfer learning methods #transfer learning resources

sophia tondon

sophia tondon


5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

#machinelearningapps #machinelearningdevelopers #machinelearningexpert #machinelearningexperts #expertmachinelearningservices #topmachinelearningcompanies #machinelearningdevelopmentcompany

Visit Blog- https://www.xplace.com/article/8743

#machine learning companies #top machine learning companies #machine learning development company #expert machine learning services #machine learning experts #machine learning expert

Jackson  Crist

Jackson Crist


Intro to Reinforcement Learning: Temporal Difference Learning, SARSA Vs. Q-learning

Reinforcement learning (RL) is surely a rising field, with the huge influence from the performance of AlphaZero (the best chess engine as of now). RL is a subfield of machine learning that teaches agents to perform in an environment to maximize rewards overtime.

Among RL’s model-free methods is temporal difference (TD) learning, with SARSA and Q-learning (QL) being two of the most used algorithms. I chose to explore SARSA and QL to highlight a subtle difference between on-policy learning and off-learning, which we will discuss later in the post.

This post assumes you have basic knowledge of the agent, environment, action, and rewards within RL’s scope. A brief introduction can be found here.

The outline of this post include:

  • Temporal difference learning (TD learning)
  • Parameters
  • QL & SARSA
  • Comparison
  • Implementation
  • Conclusion

We will compare these two algorithms via the CartPole game implementation. This post’s code can be found here :QL code ,SARSA code , and the fully functioning code . (the fully-functioning code has both algorithms implemented and trained on cart pole game)

The TD learning will be a bit mathematical, but feel free to skim through and jump directly to QL and SARSA.

#reinforcement-learning #artificial-intelligence #machine-learning #deep-learning #learning