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If you haven’t already had a chance to look at Learn Data Science From These GitHub Repositories, check it out. You may find some of the GitHub repositories mentioned useful to your machine learning journey.

Knowing data science to the core will help your machine learning career excel. As you’re trying to work towards your machine learning goals this new year, you may be tempted by the online courses and BootCamps that are popping up. It can be difficult to choose the right one, and it can be costly when you keep on choosing the wrong one. 

Another option, which provides valuable resources and comes at no to little cost is using GitHub repositories.GitHub is easy to use, supports both public and private repositories, and the major plus is that it's free on small-scale projects. 

Below is a list of GitHub repositories that can help you in your machine learning journey. 

GitHub community

Repository link: GitHub community

I will start off with the GitHub community. It was built to help support GitHub users with their educational journey. We all know that when taking on a new skill, you will have questions and problems that need to be resolved. 

Data scientists and machine learning engineers frequently use GitHub, therefore it would be valuable for you to know how it operates. This GitHub community will provide you with access to valuable resources, learn from other users, as well as ask questions and be part of an inspirational community. 

Awesome Machine Learning

Repository link: Awesome Machine Learning

An amazing curated list of machine learning frameworks, libraries and software to help you kickstart your career in machine learning. The good thing about this repository is that it is split up by language - making it easier to find the resources needed for your chosen programming language. 

It is one of the most popular learning resources as it dives deep into the technical side of machine learning. 

Machine Learning Tutorials

Repository link: Machine Learning Tutorials 

If you are the type of person that needs a tutorial in order to help you process and learn effectively - this GitHub repository is for you. This repository provides you with a list of tutorials broken down by topic. Topics include Interview Resources, Artificial Intelligence, Statistics, Classification, Deep Learning, Computer Vision, Random Forest, and more. 

If you need a brush on some topics in data science, they also have a collection of Data Science Tutorials using R and Python.

Best of ML with Python

Repository link: Best of ML with Python

I mentioned this repository in Learn Data Science From These GitHub Repositories as it was valuable to data science learning. 

The Best of ML with Python GitHub repository has 910 open-source projects that are grouped into 34 categories. The projects are ranked by a project-quality score, allowing you to easily navigate towards the popular projects. You have a variety of projects to work through and test your skills, understand your strength and focus on your weaknesses. 

TensorFlow Examples

Repository link: TensorFlow Examples

If you’re thinking about getting into machine learning, you will hear a lot about TensorFlow, and you will be using it. TensorFlow is one of the most popular machine learning frameworks out there and is vital to your skillset as a machine learning engineer. 

There is a Prerequisite section, to help you start and then there are 6 sections: introduction, Basic Models, Neural Networks, Utilities, Data Management, and Hardware. 

Projects

Applying your skills to projects will test how well your machine learning journey has been going. Projects are important for your personal learning growth but are also vital during the job search/interview stage. Recruiters and employers will want to see your skills executed in real-world projects in order for them to gauge if you’re a suitable candidate for their company. 

Here are two GitHub repositories that provide a list of machine learning-related projects: 

• https://github.com/lukas/ml-class
• https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects

Machine Learning Interview

Repository link: Machine Learning Interview

When you’re feeling confident with your machine learning skillset and have applied it to a variety of projects - your next step is to prepare for an interview. This GitHub repository is a study plan for machine learning interviews. 

Knowing the type of topics that will pop up in an interview is a better way to prepare for them, rather than going over interview questions again and again till you memorise them. This helps you learn the context and be prepared for any question surrounding that topic.

Conclusion

These GitHub repositories mentioned will provide you will the resources you require in order to become a machine learning engineer. 

If you need some guidance and structure to your learning roadmap, have a read of this: 

The Complete Machine Learning Study Roadmap.

If you’re a bookworm and prefer to learn this way, have a read of this: 15 Free Machine Learning and Deep Learning Books
 
 
Nisha Arya is a Data Scientist and Freelance Technical Writer. She is particularly interested in providing Data Science career advice or tutorials and theory based knowledge around Data Science. She also wishes to explore the different ways Artificial Intelligence is/can benefit the longevity of human life. A keen learner, seeking to broaden her tech knowledge and writing skills, whilst helping guide others.