150+ Machine Learning, NLP, and Python Tutorials - [Resources]

Robbie Allen, founder at AInsights and writer at Unsupervised Methods, has published his list of more than 150 resources for machine learning, natural language processing, and Python programming.

In Allen's own words:

"As I prepare to start my Ph.D. program in the Fall, I’ve been scouring the web for good resources on all aspects of machine learning and NLP...To help others that are going through a similar discovery process, I’ve put together a list of the best tutorial content that I’ve found so far...My goal was to link to the best tutorials I found on the important subtopics within machine learning and NLP." [source]

Some of the major topics in Allen's resource list are:

general machine learning
activation and loss functions
bias
the perceptron
regression
gradient descent
generative learning, support vector machines, and backpropagation
deep learning
TensorFlow and Pytorch
Maths, including linear algebra, statistics and calculus
and more.

I guess one could use this extensive list as a path to achieve a deep understanding of machine learning concepts. If I were to do that, here's how I'd start:

First, I would get into the general machine learning tutorials to get an insight on the mathematics behind it, then I'd go into the math section, followed by general Python, followed by tutorials on regression, gradient descent and the rest of the algorithms. Then I would start with TensorFlow and Pytorch, and then I would go into the deep learning tutorials (including everything that is related to it). Lastly I would do the NLP section.

If you think this is something for you, see the complete list of resources here:

150+ Machine Learning, NLP, and Python Tutorials