## Index of Best AI/Machine Learning Resources

Artificial Intelligence/Machine Learning field is is one of the most exciting fields in the world as of now and getting a great deal of consideration at the present time, and knowing **where to begin** can be somewhat troublesome.

I’ve been fiddling with this field, so I thought of curating the best AI/ML assets in one place. These are curated in light of if it’s a moving perused or a significant asset. I trust this curated list enable you to begin on what you have to think about AI/Machine Learning on a **specialized** level.

I have found some of very interesting and useful articles covering very basics to intermediate aspects of **AI ,Machine Learning,Deep Learning,Python,Maths** around the web.

**Best FREE Courses on AI/ML/DL (MUST SEE)**

Machine Learning Crash courses from Berkeley **Tutorial-1 Tutorial-2 Tutorial-3**

**Free Machine Learning online course (MOOC) **over 4+ Million views

**Free Machine Learning Course materials with Slides & Video Recordings: 2014-2015**

**Machine Learning Foundations: A Case Study Approach from Coursera**

**Neural Networks for Machine Learning from Coursera **

**Machine Learning from Standford **

**Coursera — Machine Learning (Andrew Ng)**

**Coursera — Neural Networks for Machine Learning (Geoffrey Hinton)**

**Udacity — Intro to Machine Learning (Sebastian Thrun)**

**Udacity — Machine Learning (Georgia Tech)**

**Udacity — Deep Learning (Vincent Vanhoucke)**

**Machine Learning (mathematicalmonk) **

**Practical Deep Learning For Coders (Jeremy Howard & Rachel Thomas)**

**Stanford CS231n — Convolutional Neural Networks for Visual Recognition (Winter 2016) (class link)**

**Stanford CS224n — Natural Language Processing with Deep Learning (Winter 2017) (class link) **

**Oxford Deep NLP 2017 (Phil Blunsom et al.)**

**Reinforcement Learning (David Silver) **

**Practical Machine Learning Tutorial with Python (sentdex)**

**Best**** Videos**** ****on ****AI/ML/DL** (**Must Watch**)

**Top 10 Best Deep Learning Videos, Tutorials & Courses on Youtube from 2017**

**10 Free Training Courses on Machine Learning and Artificial Intelligence**

**Top 50 Recent Neural Networks Videos**

**Neural Network that Changes Everything – Computerphile**

**MIT Introduction to Deep Learning and Self-Driving Cars**

**Andrew Ng: Artificial Intelligence is the New Electricity**

**Machine learning & art – Google I/O 2016**

**Best YouTube channels (FREE) **

**Machine Learning Recipes with Josh Gordon**

**Artificial Intelligence — Topic **

**Understanding Machine Learning — Shai Ben-David **

**Best Tutorials on ML**

**gentle-guide-to-machine-learning**

** The world’s easiest introduction to Machine Learning (machine-learning-is-fun) **

**Machine Learning Tutorial with Examples **

**machine-learning-algorithm-use**

**Best Tutorials on Neural networks**

**Role of Bias in Neural Networks **

**What is bias in artificial neural network? **

**Single-layer Neural Networks (Perceptrons) **

**From Perceptrons to Deep Networks**

## **Best Tutorials on Deep Learning**

**What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning? **

**Deep Learning for NLP (without Magic) **

**Understanding Convolutional Neural Networks for NLP **

**Deep Learning, NLP, and Representations **

**Embed, encode, attend, predict: The new deep learning formula for state-of-the-art NLP models **

**Understanding Natural Language with Deep Neural Networks Using Torch**

**Deep Learning for NLP with Pytorch **

## **Best Tutorials on NLP**

**A Primer on Neural Network Models for Natural Language Processing**** **

**The Definitive Guide to Natural Language Processing**

**Introduction to Natural Language Processing **

**Natural Language Processing Tutorial **

**Natural Language Processing (almost) from Scratch**

**Best Tutorials on Techniques of Machine Learning ****Process: **

**Support Vector Machines**

**An introduction to Support Vector Machines (SVM) **

**Linear classification: Support Vector Machine, Softmax**

## **Gradient Descent**

**Learning with gradient descent**

**How to understand Gradient Descent algorithm **

**An overview of gradient descent optimization algorithms**

**Optimization: Stochastic Gradient Descent**

## **Regression**

**Introduction to linear regression analysis**

**Simple Linear Regression Tutorial for Machine Learning**

**Logistic Regression Tutorial for Machine Learning**

## **Backpropagation**

**Yes you should understand backprop**

**Can you give a visual explanation for the back propagation algorithm for neural networks? **

**How the backpropagation algorithm works**

**Backpropagation Through Time and Vanishing Gradients **

**A Gentle Introduction to Backpropagation Through Time**

## **Optimization and Dimensionality Reduction**

**Seven Techniques for Data Dimensionality Reduction**

**Dropout: A simple way to improve neural networks **

**How to train your Deep Neural Network**

## **Long Short Term Memory (LSTM)**

**A Gentle Introduction to Long Short-Term Memory Networks by the Experts**

**Anyone Can Learn To Code an LSTM-RNN in Python**

## **Convolutional Neural Networks (CNNs)**

**Introducing convolutional networks**

**Deep Learning and Convolutional Neural Networks**

**Conv Nets: A Modular Perspective **

## **Recurrent Neural Nets (RNNs)**

**Recurrent Neural Networks Tutorial**

**Attention and Augmented Recurrent Neural Networks **

**The Unreasonable Effectiveness of Recurrent Neural Networks**

**A Deep Dive into Recurrent Neural Nets**

## **Reinforcement Learning**

**Simple Beginner’s guide to Reinforcement Learning & its implementation**

**A Tutorial for Reinforcement Learning **

**Learning Reinforcement Learning **

**Deep Reinforcement Learning: Pong from Pixels**

## **Generative Adversarial Networks (GANs)**

**What’s a Generative Adversarial Network? **

**Abusing Generative Adversarial Networks to Make 8-bit Pixel Art**

**An introduction to Generative Adversarial Networks (with code in TensorFlow) **

**Generative Adversarial Networks for Beginners**

## **Word Vectors**

**Bag of Words Meets Bags of Popcorn**

**On word embeddings Part I, Part II, Part III **

**The amazing power of word vectors **

**word2vec Parameter Learning Explained **

**Word2Vec Tutorial — The Skip-Gram Model, Negative Sampling**

## **Encoder-Decoder**

**Attention and Memory in Deep Learning and NLP**

**Sequence to Sequence Learning with Neural Networks **

**Machine Learning is Fun Part 5: Language Translation with Deep Learning and the Magic of Sequences **

**How to use an Encoder-Decoder LSTM to Echo Sequences of Random Integers**

**AI R&D Organizations**

**Python**

**A Complete Guide on Getting Started with Deep Learning in Python**

**7 Steps to Mastering Machine Learning With Python **

**An example machine learning notebook **

**How To Implement The Perceptron Algorithm From Scratch In Python**

**Implementing a Neural Network from Scratch in Python **

**A Neural Network in 11 lines of Python**

**Implementing Your Own k-Nearest Neighbour Algorithm Using Python**

**Demonstration of Memory with a Long Short-Term Memory Network in Python **

**How to Learn to Echo Random Integers with Long Short-Term Memory Recurrent Neural Networks **

**How to Learn to Add Numbers with seq2seq Recurrent Neural Networks**

**Scipy and numpy**

**An introduction to Numpy and Scipy **

**A Crash Course in Python for Scientists**

## **scikit-learn**

**PyCon scikit-learn Tutorial Index **

**scikit-learn Classification Algorithms **

**Abridged scikit-learn Tutorials**

## **PyTorch**

**Tutorial: Deep Learning in PyTorch **

**PyTorch Tutorial for Deep Learning Researchers**

**Tensorflow**

**learn-tensorflow-and-deep-learning-without-a-phd**

**Introduction to TensorFlow — CPU vs GPU **

**Implementing a CNN for Text Classification in TensorFlow **

** How to Run Text Summarization with TensorFlow**

## **Math**

## **Linear algebra**

**An Intuitive Guide to Linear Algebra**

**A Programmer’s Intuition for Matrix Multiplication **

**Understanding the Cross Product **

**Linear Algebra for Machine Learning **

**Linear algebra cheat sheet for deep learning **

**Linear Algebra Review and Reference **

## **Probability**

**Understanding Bayes Theorem With Ratios**

**Review of Probability Theory (Stanford CS229)**

**Probability Theory Review for Machine Learning (Stanford CS229)**

**Probability Theory (U. of Buffalo CSE574)**

**Probability Theory for Machine Learning (U. of Toronto CSC411)**

## **Calculus**

**How To Understand Derivatives: The Quotient Rule, Exponents, and Logarithms **

** How To Understand Derivatives: The Product, Power & Chain Rules**

**Vector Calculus: Understanding the Gradient **

**Miscellaneous**

**15 Algorithms Machine Learning Engineers Must Need to Know**

**An Overview of Multi-Task Learning in Deep Neural Networks**

**Top & Best Artificial Intelligence Products/Companies**

**Best 2017 Artificial Intelligence Videos Playlist**

**A List of Free AI Software Programs to Download**

**Essential Cheat Sheets for Machine Learning Python and Maths**

**List of 10 Free Must-Read Books for Machine Learning**

**CONCLUSION**

On the off chance that there are great instructional exercises you know about that I’m missing, please inform me!

I’m endeavoring to restrict only important instructional exercises since much past that would be tedious. Each weblink ought to have **diverse materia**l from alternate connections or present data in an unexpected way.

**Related:**

**HOW TO LEARN MACHINE LEARNING IN 90 DAYS**

**6 Easy Steps To Get Started Learning Artificial Intelligence**

** A Complete Guide on Getting Started with Deep Learning **

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