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I'm not sure if this is the right place to ask this question, but is there any online source that provides a complete in-depth explanation of Machine Learning algorithms, all at one place, but not too complicated for a beginner to understand?

Every source I refer to either covers the topics superficially or focuses on only one aspect of the algorithm which makes me waste a big chunk of my study time going through different websites & videos looking for the same.

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How to Learn Data Science For Free

Python Corey Schafer https://www.youtube.com/user/schafer5 Sentdex https://www.youtube.com/user/sentdex Machine Learning with Maths, Statistics and Linear Algebra Andrew NG applied AI https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN Krish Naik https://www.youtube.com/watch?v=EqRsD3gqeCo&list=PLZoTAELRMXVOnN_g96ayzXX5i7RRO0QhL

Sentdex https://www.youtube.com/user/sentdex

Statquest with Josh Starmer https://www.youtube.com/user/joshstarmer

Natural Language Processing Krish https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm Sentdex https://www.youtube.com/user/sentdex

Deep Learning Andrew Ng https://www.youtube.com/watch?v=CS4cs9xVecg&list=PLkDaE6sCZn6Ec-XTbcX1uRg2_u4xOEky0 Krish Naik https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi

Data Science Projects https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

Blogs that are freely Available https://towardsdatascience.com/ https://medium.com/topic/machine-learning

Feature Engineering Playlist https://github.com/aikho/awesome-feature-engineering

Feature Selection Playlist https://github.com/anujdutt9/Feature-Selection-for-Machine-Learning

Krish Naik Featured Engineering: https://github.com/krishnaik06/Complete-Feature-Engineering https://github.com/krishnaik06/Feature-Engineering

Book (Python For Finance) https://github.com/PacktPublishing/Hands-on-Python-for-Finance

Kaggle Solution http://ndres.me/kaggle-past-solutions/

How to Learn Data Science For Free.docx Ref : https://www.kaggle.com/getting-started/113420

For more advanced resources visit this link

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Check out scikit-learn. It is a python library which implements many ML algorithms and describes how they work to some extent.

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This is excellent, for beginners, intermediate level users, and experts too!

https://scikit-learn.org/stable/user_guide.html

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The following are 2 handy reference books on ML and Deep Learning. There should be some free pdf versions that you can download on the web.

  1. Introduction to Machine Learning with Python by Andreas C. Müller and Sarah Guido https://pdfroom.com/books/introduction-to-machine-learning-with-python-a-guide-for-data-scientists/qjb5q6ykdxQ

  2. Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow by Aurélien Géron

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Have a look at „Introduction to Statistical Learning“. This book is for beginners but written by top academics. It comes with R „labs“ (also Python version available), so that you can try things out and learn R if you don‘t do it already.

In case you want to dig deeper into one or another topic, you may refer to „Elements of Statistical Learning“ which is like the „grown-up“ counterpart to ISL.

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If you are looking for practical python examples, check out this website with multiple programming examples for beginners.

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