Learn About GitHub CodeSpace

In this post, we will be looking at the flaws of the traditional development environment and then GitHub Codespaces and the good stuff it has in store for developers. Without any further ado, let’s get started.



What is GEEK

Buddha Community

Learn About GitHub CodeSpace
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

E-learning Software Services - SISGAIN

SISGAIN is one of the top e-Learning software companies in New York, USA. Develop Education Technology based, mobile application for e-learning from SISGAIN. We Develop User Friendly Education App and Provide e-learning web portals development Service. Get Free Quote, Instant Support & End to End Solution. SISGAIN has been developing educational software and provides e-learning application development services for US & UK clients. For more information call us at +18444455767 or email us at hello@sisgain.com

#learning development companies #development of software for e-learning #top e-learning software companies #e-learning web portals #mobile applications for e-learning #e-learning product development