Find The Most Updated and Free Artificial Intelligence, Machine Learning, Data Science, Deep Learning, Mathematics, Python Programming Resources. (Last Update: Feb 14, 2021)
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Deep Learning Resources
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Data Science Resources
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CS109 Data Science- Harvard
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Data Science Essentials- Microsoft
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Learning from Data – California Institute of Technology
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The Mathematics of Machine Learning by UC Berkeley
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"Foundations of Data Science" Book by Avrim Blum, John Hopcroft, and Ravindran Kannan
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Python Data Science Handbook by Jake VanderPlas
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Set of animated Artificial Intelligence cheatsheets covering the content of Stanford's CS 221 class:
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Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science: MIT
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Python for Data Analysis by Boston University (Credit: Katia Oleinik)
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Data Mining: University at Buffalo
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MIT: The Missing Semester of Your CS Education
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FREE SQL FOR DATA SCIENCE COURSE: Datamoves
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SQL Zoo: Learn SQL in stages
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Bayesian Data Analysis course
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MIT: Introduction to Computational Thinking with Julia, with Applications to Modeling the COVID-19 Pandemic
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Machine Learning Resources
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Introduction to Statistical Machine Learning Notes by Andreas Lindholm, Uppsala University
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Machine Learning Crash Course with TensorFlow APIs by Google
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The Mathematics of Machine Learning by UC Berkeley
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Understanding the major types of machine learning
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Self Supervised Learning 122 page lecture notebook by Andrew Zisserman from Deepmind and University of Oxford
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Stanford Machine Learning Notes From Andrew NG
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Machine Learning Use Case in Google, Facebook, Amazon, Microsoft, Kaggle, General Electric, and Cornerstone
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Understanding Machine Learning: From Theory to Algorithms (FREE book pdf)
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Set of animated Artificial Intelligence cheatsheets covering the content of Stanford's CS 221 class:
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Samsung AI lab develops tech that can animate highly realistic heads using only a few -or in some cases - only one starter image.
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Stanford's CS230 Deep learning lecture videos and more
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AI For Everyone [Deeplearning.ai]
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FOUNDATIONS OF MACHINE LEARNING- BLOOMBERG
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Introduction to Machine Learning. (Free) Code and Tutorials included (Github)
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Machine Learning Math Notations. By Shan Hung-Wu
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Stanford Machine Learning Class Notes (CS229)
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ML Crash Course- Microsoft
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AI Developer Bootcamp- Microsoft
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Machine Learning Projects With Python By Lisa Taglieferri
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Intel AI Developer Program
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Concise Machine Learning (UC Berkeley Notes)
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Applying Unsupervised Learning - MathWorks
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Machine Learning for Intelligent Systems-Cornell CS4780/CS5780
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AI Demystified: 5-Day Mini-Course
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Statistics and Machine Learning in Python Release 0.3 beta
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Introduction to Machine Learning Course : University at Buffalo
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Finland's Free AI Courses
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Machine Learning From Scratch: GitHub, by Erik Linder-Norén
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CS 188 : Introduction to Artificial Intelligence: Pieter Abbeel & Dan Klein, University of California, Berkeley
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Machine Learning : University of Oxford 2015
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Understanding Machine Learning 2014 Course Lecture Notes and Videos
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Mathematics for Machine Learning (Book)
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CS221: Artificial Intelligence: Principles and Techniques (Stanford)
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CS229 Machine Learning (Stanford)
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Master Machine Learning from University of Washington. Enroll today! (Sponsored Link)
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Andrew Ng' Machine Learning: Master the Fundamentals (Audit the course)
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Pattern Recognition and Machine Learning: Book
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MIT: The Missing Semester of Your CS Education
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Machine Learning for Everyone
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Concise Machine Learning (University of California at Berkeley)
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Start Here with Machine Learning (machinelearningmastery.com)
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Machine Learning From Scratch by Erik Linder-Norén (Machine Learning Engineer at Apple)
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Machine Learning from Scratch- Free Book
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MIT: Introduction to Computational Thinking with Julia, with Applications to Modeling the COVID-19 Pandemic
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Deep Learning Resources
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Deep Learning Tools with Process [Picture]
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The Mathematics of Machine Learning by UC Berkeley
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Self Supervised Learning 122 page lecture notebook by Andrew Zisserman from Deepmind and University of Oxford
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CS 294-112. Deep Reinforcement Learning by Sergey Levine. UC Berkeley. Fall 2018
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Illustrated Deep Learning cheatsheets covering Stanford's CS 230 class
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Set of animated Artificial Intelligence cheatsheets covering the content of Stanford's CS 221 class:
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Samsung AI lab develops tech that can animate highly realistic heads using only a few -or in some cases - only one starter image.
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Stanford's CS230 Deep learning lecture videos and more
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AI For Everyone [Deeplearning.ai]
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MIT 6.S094: Deep Learning for Self-Driving Cars
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Neural Networks for Machine Learning — Geoffrey Hinton 2016
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EE-559 – DEEP LEARNING (SPRING 2018) EPFL
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Part 2: Deep Learning from the Foundations(2019) by Fast.ai
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Neural networks class by Hugo Larochelle from Université de Sherbrooke
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Build a Predictive Maintenance Solution using Deep Learning
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AI Developer Bootcamp- Microsoft
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Mathematics for Machine Learning Specialization (Imperial College)
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Intel AI Developer Program
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Dive into Deep Learning (Book): Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola
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Course: Deep Learning in Computer Vision (with Prof. Kosta Derpanis (Ryerson University))
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Deep Learning: University at Buffalo
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DLAI - Deep Learning for Artificial Intelligence @ UPC Barcelona
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Hardware Accelerators for Training Deep Neural Networks: Stanford
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MIT lecture series on deep learning:Basics
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MIT lecture series on deep learning: State of the Art
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MIT lecture series on deep learning: Introduction to Deep RL
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CS224N: Natural Language Processing with Deep Learning | Winter 2019 | Stanford
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CS230 Deep Learning (Stanford)
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MIT 6.S191 Introduction to Deep Learning
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CS231n: Convolutional Neural Networks for Visual Recognition
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MIT: The Missing Semester of Your CS Education
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Introduction to Deep Learning (I2DL) (IN2346): Prof. Matthias Nießner
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Free Deep Learning Resources (FAU Pattern Recognition Lab)
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Advanced Deep Learning for Computer vision (ADL4CV) (IN2364)
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Neural Networks and Introduction to Deep Learning (WikiStat)
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MIT: Introduction to Computational Thinking with Julia, with Applications to Modeling the COVID-19 Pandemic
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MIT\'s introductory bootcamp on deep learning methods
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Mathematics
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The Mathematics of Machine Learning by UC Berkeley
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Computer Age Statistical Inference - Algorithms, Evidence, & Data Science (FREE book pdf for personal use)
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Statistical Learning- Classification
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Machine Learning Math Notations. By Shan Hung-Wu
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Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science: MIT
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A Beginner\'s Guide to the Mathematics of Neural Networks (Kings College London)
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Brandon Foltz\' Stats 101
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Duke University\'s Introduction to Probability and Data on Coursera
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Khan Academy\\\\\\\'s Statistics and Probability Course
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Introduction to Probability by Harvard
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Stats 100 Final Cheat Sheets -Fas Harvard
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Linear Algebra Book (Free Version) by Jim Hefferon
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Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares[Book-Stanford]
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Statistics and Machine Learning in Python Release 0.3 beta
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Probabilistic Graphical Models Course: University at Buffalo
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Introduction to Applied Linear Algebra Vectors, Matrices, and Least Squares: Book
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\"Elements of Statistical Learning\" by Hastie.: Book
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An Introduction to Statistical Learning (Free Book)
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Mathematics for Machine Learning (Book)
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MIT: The Missing Semester of Your CS Education
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Backpropagation, Intuitions (Stanford CS231n)
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A Beginner\'s Guide to the Mathematics of Neural Networks (King\'s College London)
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MATH 3070 (Applied Statistics I) University of Utah
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Reinforcement Learning
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CS 294-112. Deep Reinforcement Learning by Sergey Levine. UC Berkeley. Fall 2018
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Samsung AI lab develops tech that can animate highly realistic heads using only a few -or in some cases - only one starter image.
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CS885 Reinforcement Learning - Spring 2018 - University of Waterloo
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CS234: Reinforcement Learning
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Reinforcement Learning by IIT Madras
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David Silver\'s course link
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Deep RL Bootcamp
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Intel AI Developer Program
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Introduction to Reinforcement Learning: Deepmind
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REINFORCEMENT LEARNING AND OPTIMAL CONTROL BOOK, VIDEOLECTURES, AND COURSE MATERIAL, 2019
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MIT: The Missing Semester of Your CS Education
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Python
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Python Data Science Handbook by Jake VanderPlas
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Pythonic Data Cleaning With NumPy and Pandas
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Python for Data Analysis by Boston University (Credit: Katia Oleinik)
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Machine Learning Projects With Python By Lisa Taglieferri
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Introduction Programming in Python
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Python code for Artificial Intelligence - David Poole & Alan Mackworth
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Statistics and Machine Learning in Python Release 0.3 beta
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Master Python in 5 Online Courses from University of Michigan. Enroll today! (Advertisement)
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MIT: The Missing Semester of Your CS Education
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