Data Science
Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.
Teach yourself !
DS /ML Podcast fast.ai Support us on Patreon !
Udacity Machine Learning By Georgia Tech
This class is offered as CS7641 at Georgia Tech where it is a part of the Online Masters Degree (OMS). Machine Learning is a graduate-level course covering the area of Artificial Intelligence concerned with computer programs that modify and improve their performance through experiences. The first part of the course covers Supervised Learning, a machine learning task that makes it possible for your phone to recognize your voice, your email to filter spam, and for computers to learn a bunch of other cool stuff. In part two, you will learn about Unsupervised Learning. Ever wonder how Netflix can predict what movies you'll like? Or how Amazon knows what you want to buy before you do? Such answers can be found in this section!Finally, can we program machines to learn like humans? This Reinforcement Learning section will teach you the algorithms for designing self-learning agents like us!
Machine Learning Crash Course By Google
A self-study guide for aspiring machine learning practitioners Machine Learning Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.
FreeCodeCamp.org Machine Learning
Learn how to use TensorFlow 2.0 for machine learning in this MASSIVE free course
Crash Course AI
In 20 episodes, Jabril will teach you about Artificial Intelligence and Machine Learning! This course is based on a university-level curriculum. By the end of the course, you will be able to: * Define, differentiate, and provide examples of Artificial Intelligence and three types of Machine Learning: supervised, unsupervised, and reinforcement * Understand how different AI and ML approaches can be combined to create compelling applications such as natural language processing, robotics, recommender systems, and web search * Implement several types of AI to classify images, generate text from examples, play video games, and recommend content based on past preferences * Understand the causes of algorithmic bias and audit datasets for several of these causes * Reason about how specific advances in AI may impact our world and your life, for better or for worse
Machine Learning FreeCodeCamp Guide
Machine learning is exactly like how a human being learns. For example if a human wants to learn how to play poker, it will firstly learn the rules. Then it will try to get experience by playing the game. This experience is nothing but a huge data set for a machine by using which it can make intelligent decisions reagrding the proposed problem.
My Python YouTube Videos
Learn Python for machine learning
Intro To Machine Learning Udacity!
Machine Learning is a first-class ticket to the most exciting careers in data analysis today. As data sources proliferate along with the computing power to process them, going straight to the data is one of the most straightforward ways to quickly gain insights and make predictions.
Machine learning brings together computer science and statistics to harness that predictive power. It’s a must-have skill for all aspiring data analysts and data scientists, or anyone else who wants to wrestle all that raw data into refined trends and predictions.
Intro to Data Science
The Introduction to Data Science class will survey the foundational topics in data science, namely:
Data Manipulation
Data Analysis with Statistics and Machine Learning
Data Communication with Information Visualization
Data at Scale -- Working with Big Data
The class will focus on breadth and present the topics briefly instead of focusing on a single topic in depth. This will give you the opportunity to sample and apply the basic techniques of data science.
Intro to Data Analysis Udacity!
This course will introduce you to the world of data analysis. You'll learn how to go through the entire data analysis process, which includes:
Posing a question
Wrangling your data into a format you can use and fixing any problems with it
Exploring the data, finding patterns in it, and building your intuition about it
Drawing conclusions and/or making predictions
Communicating your findings
You'll also learn how to use the Python libraries NumPy, Pandas, and Matplotlib to write code that's cleaner, more concise, and runs faster.
fast.ai
fast.ai is dedicated to making the power of deep learning accessible to all. Deep learning is dramatically improving medicine, education, agriculture, transport and many other fields, with the greatest potential impact in the developing world. For its full potential to be met, the technology needs to be much easier to use, more reliable, and more intuitive than it is today.
Data Camp
Learn Data Science Online Everyday, massive amounts of data are generated in every part of our lives. That makes data fluency an indispensable skill to help you succeed - no matter what industry you’re in. At DataCamp, we’re here to help, whether you're just getting started or are looking to dig deeper.
Kaggle
The Home of Data Science & Machine Learning Kaggle helps you learn, work, and play
IBM Watson
Use IBM Watson to collaborate and build smarter applications. Quickly visualize and discover insights from your data and collaborate across teams.
CV-Tricks
In this Tensorflow tutorial, we shall build a convolutional neural network based image classifier using Tensorflow. If you are just getting started with Tensorflow, then it would be a good idea to read the basic Tensorflow tutorial here. To demonstrate how to build a convolutional neural network based image classifier, we shall build a 6 layer neural network that will identify and separate images of dogs from that of cats. This network that we shall build is a very small network that you can run on a CPU as well. Traditional neural networks that are very good at doing image classification have many more paramters and take a lot of time if trained on CPU. However, in this post, my objective is to show you how to build a real-world convolutional neural network using Tensorflow rather than participating in ILSVRC. Before we start with Tensorflow tutorial, let’s cover basics of convolutional neural network. If you are already familiar with conv-nets(and call them conv-nets), you can move to part-2 i.e. Tensorflow tutorial
Deep Learning MIT Press
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free.
Siraj Raval YouTube
I'm Siraj. I'm on a warpath to inspire and educate developers to build Artificial Intelligence. Games, music, chatbots, art, i'll teach you how to make it all yourself. We are the fastest growing AI community in the world. Our mission: Solve AI. Use it to benefit humanity.
Databricks
Databricks Unified Analytics Accelerate innovation by unifying data science, engineering and business
Udacity Intro to Statistics
Making Decisions Based on Data
Andrew Ng Machine Learning Course
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.
Foundations of Data Science: Prediction and Machine Learning
Learn how to use machine learning, with a focus on regression and classification, to automatically identify patterns in your data and make better predictions.
UC Berkeley CS188 Intro to AI -- Course Materials
For artificial intelligence: do Berkeley’s intro to AI course by watching the videos and completing the excellent Pacman projects. As a textbook, use Russell and Norvig’s Artificial Intelligence: A Modern Approach.
Teach Yourself CS
If you’re a self-taught engineer or bootcamp grad, you owe it to yourself to learn computer science. Thankfully, you can give yourself a world-class CS education without investing years and a small fortune in a degree program 💸. There are plenty of resources out there, but some are better than others. You don’t need yet another “200+ Free Online Courses” listicle. You need answers to these questions
School of AI - Udacity
AI is one of the fastest-growing and most transformational technologies of our time, with 2.3 million new jobs opening up by 2020. In 10 hours a week, master in-demand skills and access a new world of opportunities.
Siraj School of AI
School of AI Siraj
Machine Learning Algorithms Wiki
While Deeplearning4j and its suite of open-source libraries - ND4J, DataVec, Arbiter, etc. - primarily implement scalable, deep artificial neural networks, developers can also work with more traditional machine-learning algorithms using our framework.
Elite Datascience
8 Fun Machine Learning Projects !
Chad W Gardner
RESOURCES – FOR FREE! Here is a mostly random, hopefully useful hodgepodge of resources, articles, podcasts and more that Chad has collected over the last few months. Happy digging, and check back often!
Microsoft and EdX
The AI track takes aspiring AI engineers from a basic introduction of AI to mastery of the skills needed to build deep learning models for AI solutions that exhibit human-like behavior and intelligence.
DeepLearning.AI
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects.
Advanced Data Science with IBM Specialization
As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You'll understand the mathematical foundations behind all machine learning & deep learning algorithms.
Kaggle Python Free Course
Learn the most important language for Data Science
Lyrebird.ai
Create the most realistic artificial voices in the world
DeepArt.io
TURN ANY PHOTO INTO AN ARTWORK – FOR FREE! We use an algorithm inspired by the human brain. It uses the stylistic elements of one image to draw the content of another. Get your own artwork in just three steps.
Open AI
Discovering and enacting the path to safe artificial general intelligence.
Open AI Gym
Gym is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents everything from walking to playing games like Pong or Pinball.
BOOKS
Python Data Science Handbook
This repository contains the full listing of IPython notebooks used to create the book, including all text and code. The code was written and tested with Python 3.5, though most (but not all) snippets will work correctly in Python 2.7.
Artificial Intelligence with Python
This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks.
Data Science Articles
My Data Science Master's by Davud Venturi
He dropped out of school to create his own Data Science Master's Degree Curriculum Online. In this article you can see what free and paid online material he used for his curriculum.
How To Become A Data Analyst
Data analysts collect, process and perform statistical analyses of data. Their skills may not be as advanced as data scientists (e.g. they may not be able to create new algorithms), but their goals are the same – to discover how data can be used to answer questions and solve problems.
Data Science vs. Big Data vs. data Analytics
Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. According to IBM, 2.5 billion gigabytes (GB) of data was generated every day in 2012.
Best Big Data Certifications
Today's organizations are looking for more and better ways to pull out the information they need from the massive volume of data available to them. Big data system administrators store, manage and transfer large sets of data, making them amenable to analysis. Data analytics is the practice of examining the raw data to identify patterns and draw conclusions. Business intelligence involves the collection and organization of information to report on business activities, often pulling data from those very sets.
Predictive Analytics in 2018: Salaries & Industry Shifts
Our salary studies report base salary variations of predictive analytics professionals, both individual contributors and managers, as well as the proportions eligible for a bonus, and the median and mean bonuses received. We also report how base salaries have changed since last year’s study. Finally, the report explains how salaries of predictive analytics professionals vary based on several characteristics including job level, industry, region, education, residency status, and gender.