Paid courses completely failed to teach me how machine learning works.
I used to just import scikit-learn and call model. fit.
So I spent 6 months studying the most popular models.
Here are the 7 resources I used to get ahead:
I used to just import scikit-learn and call model. fit.
So I spent 6 months studying the most popular models.
Here are the 7 resources I used to get ahead:
Interpretable Machine Learning
A Guide for Making Black Box Models Explainable
A must-read for any data scientist that needs to explain their models:
christophm.github.io
A Guide for Making Black Box Models Explainable
A must-read for any data scientist that needs to explain their models:
christophm.github.io
Made With ML
Learn how to deliver value with machine learning.
Lessons to take readers from foundations to machine learning operations (MLOps).
madewithml.com
Learn how to deliver value with machine learning.
Lessons to take readers from foundations to machine learning operations (MLOps).
madewithml.com
Awesome Deep Learning Papers
A curated list of the most cited deep learning papers (2012-2016)
These are the classic deep learning papers that are worth reading regardless of where you use deep learning.
github.com
A curated list of the most cited deep learning papers (2012-2016)
These are the classic deep learning papers that are worth reading regardless of where you use deep learning.
github.com
Machine Learning From Scratch
Python implementations of fundamental machine learning models and algorithms.
Learn the inner workings of the models you use every day.
github.com
Python implementations of fundamental machine learning models and algorithms.
Learn the inner workings of the models you use every day.
github.com
Homemade Machine Learning
Implement machine learning from scratch.
Practice implementing the most important machine learning algorithms to get a better understanding of the mathematics behind them.
github.com
Implement machine learning from scratch.
Practice implementing the most important machine learning algorithms to get a better understanding of the mathematics behind them.
github.com
Python for Data Analysis
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
github.com
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
github.com
Deep Learning with Python
This repository contains Jupyter notebooks implementing the code samples found in the book Deep Learning with Python, 2nd Edition (Manning Publications)
github.com
This repository contains Jupyter notebooks implementing the code samples found in the book Deep Learning with Python, 2nd Edition (Manning Publications)
github.com
The 7 resources that will help you apply the fundamentals:
• Awesome Deep Learning Papers
• Interpretable Machine Learning
• Machine Learning From Scratch
• Homemade Machine Learning
• Deep Learning with Python
• Python for Data Analysis
• Made With ML
🤖
• Awesome Deep Learning Papers
• Interpretable Machine Learning
• Machine Learning From Scratch
• Homemade Machine Learning
• Deep Learning with Python
• Python for Data Analysis
• Made With ML
🤖
There's enough in here to keep you reading for a while!
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Hop back to the top and retweet the top tweet so you can find it later - and so others can find it too!
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