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Linear Regression with Numpyhttps://github.com/py-ranoid/IntroML/blob/master/Week1/Linear%20Regression%20with%20Numpy.ipynb
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https://patch-diff.githubusercontent.com/GajeshS/IntroML#week-2
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https://patch-diff.githubusercontent.com/GajeshS/IntroML#resources
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pythonprogramming.nethttp://www.pythonprogramming.net
towardsdatascience.comhttp://towardsdatascience.com
machinelearningmastery.comhttp://machinelearningmastery.com
Image Search Engines and Basic Computer Visionhttp://pyimagesearch.com
https://brohrer.github.io/blog.htmlhttps://brohrer.github.io/blog.html
https://medium.freecodecamp.org/an-intuitive-guide-to-convolutional-neural-networks-260c2de0a050https://medium.freecodecamp.org/an-intuitive-guide-to-convolutional-neural-networks-260c2de0a050
http://karpathy.github.io/2015/05/21/rnn-effectiveness/http://karpathy.github.io/2015/05/21/rnn-effectiveness/
https://blog.openai.com/generative-models/https://blog.openai.com/generative-models/
https://sgugger.github.io/the-1cycle-policy.htmlhttps://sgugger.github.io/the-1cycle-policy.html
https://patch-diff.githubusercontent.com/GajeshS/IntroML#books
Deep learning bookhttp://www.deeplearningbook.org/
Speech and Language Processinghttps://web.stanford.edu/~jurafsky/slp3/
A Primer on Neural Network Models for Natural Language Processinghttp://u.cs.biu.ac.il/~yogo/nnlp.pdf
Machine Learning by Tom Mitchell.https://www.cs.ubbcluj.ro/~gabis/ml/ml-books/McGrawHill%20-%20Machine%20Learning%20-Tom%20Mitchell.pdf
https://patch-diff.githubusercontent.com/GajeshS/IntroML#courses-and-videos
Andrew NG's Course on Machine Learninghttps://www.coursera.org/learn/machine-learning
Andrew NG's Deep Learning Specialisationhttps://www.coursera.org/specializations/deep-learning
http://cs231n.github.iohttp://cs231n.github.io
http://cs229.stanford.edu/http://cs229.stanford.edu/
http://cs229.stanford.edu/syllabus.htmlhttp://cs229.stanford.edu/syllabus.html
http://web.stanford.edu/class/cs224n/http://web.stanford.edu/class/cs224n/
Practical Deep Learning for Codershttp://course.fast.ai/
Cutting Edge Deep Learning for Codershttp://course.fast.ai/part2.html
Online textbookhttps://github.com/fastai/numerical-linear-algebra/blob/master/README.md
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Natural Language Processinghttps://github.com/josephmisiti/awesome-machine-learning#natural-language-processing-10
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Here's a free, easy course that introduces you to most of these libraries.https://www.udemy.com/deep-learning-prerequisites-the-numpy-stack-in-python/learn/v4/overview
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https://www.anaconda.com/download/https://www.anaconda.com/download/
https://conda.io/docs/user-guide/install/windows.htmlhttps://conda.io/docs/user-guide/install/windows.html
https://www.rstudio.com/products/rstudio/download/https://www.rstudio.com/products/rstudio/download/
http://jupyter.org/installhttp://jupyter.org/install
https://developers.google.com/machine-learning/guides/rules-of-ml/https://developers.google.com/machine-learning/guides/rules-of-ml/
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Andrew Nghttps://twitter.com/AndrewYNg
Andrej Karpathyhttps://twitter.com/karpathy
Michael Jordanhttps://people.eecs.berkeley.edu/~jordan/?_ga=1.104786372.57480868.1488216728
Yann LeCunhttps://twitter.com/ylecun
Geoffrey Hintonhttp://www.cs.toronto.edu/~hinton/
James Chamhttps://twitter.com/jamescham
Bob Poekerthttps://twitter.com/bobpoekert?lang=en
Yoshua Bengiohttp://www.iro.umontreal.ca/~bengioy/yoshua_en/
Ian Goodfellowhttps://twitter.com/goodfellow_ian?lang=en
Siraj Ravalhttps://twitter.com/sirajraval
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