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<!DOCTYPE html>
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<title>Document</title>
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<body>
<a href="http://people.eecs.berkeley.edu/~jrs/189/"> Jonathan Shewchuk - CS 189/289A Introduction to Machine Learning</a>
<a href="http://people.csail.mit.edu/dsontag/courses/ml16/"> Prof. David Sontag - Introduction To Machine Learning - Spring 2016</a>
<a href="https://math.berkeley.edu/~nikhil/courses/53.s18/"> Nikhil Srivastava - Math 53: Multivariable Calculus. Spring 2018</a>
<a href="https://github.com/louisfb01/start-machine-learning">https://github.com/louisfb01/start-machine-learning</a>
<a href="https://www.geeksforgeeks.org/machine-learning/">https://www.geeksforgeeks.org/machine-learning/</a>
<a href="https://www.kaggle.com/thirty-days-of-ml">https://www.kaggle.com/thirty-days-of-ml</a>
<a href="https://www.fast.ai/">Making neural nets uncool again</a>
<a href="https://developers.google.com/machine-learning/crash-course/">Machine Learning Crash Course
with TensorFlow APIs || Google's fast-paced, practical introduction to machine learning ||</a>
<a href="https://github.com/llSourcell/Learn_Machine_Learning_in_3_Months">Learn_Machine_Learning_in_3_Months</a>
<a href="https://github.com/microsoft/ML-For-Beginners">12 weeks, 24 lessons, classic Machine Learning for all</a>
<a href="https://github.com/khangich/machine-learning-interview">https://github.com/khangich/machine-learning-interview</a>
<a href="https://huyenchip.com/ml-interviews-book">https://huyenchip.com/ml-interviews-book</a>
<a href="https://github.com/chiphuyen/ml-interviews-book">https://github.com/chiphuyen/ml-interviews-book</a>
<a href="https://stanford-cs329s.github.io/syllabus.html">https://stanford-cs329s.github.io/syllabus.html</a>
<a href="https://github.com/kubeflow/kubeflow">https://github.com/kubeflow/kubeflow</a>
<a href="https://github.com/stefan-jansen/machine-learning-for-trading">https://github.com/stefan-jansen/machine-learning-for-trading</a>
<a href="https://github.com/eriklindernoren/ML-From-Scratch">https://github.com/eriklindernoren/ML-From-Scratch</a>
<a href="https://dsc40a.com/pages/resources.html">Theoretical Foundations of Data Science I</a>
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