This article was posted by Ingrid Daubechies on Quanta Magazine. Ingrid is the James B. Duke Professor of Mathematics and Electrical and Computer Engineering at Duke University. She served as president of the International Mathematical Union from 2011 to 2014.

Machine learning works spectacularly well, but mathematicians aren’t quite sure why.…

This article was posted by Adam Geitgey. Adam is Interested in computers and machine learning and he likes to write about it.

Speech recognition is invading our lives. It’s built into our phones, our game consoles and our smart watches. It’s even automating our homes. For just $50, you can get an Amazon Echo Dot — a magic box that…

This article was written by S. Richter-Walsh. S. Richter-Walsh likes to write about environmental science and also enjoy posting interesting data analyses and visualisations.

Introduction

A very useful machine learning method which, for its…

This article was written by John Hammink. John is Chief Evangelist for Treasure Data. An 18-year veteran of the technology and startup scene, he enjoys travel to unusual places, as well as creating digital art and world music.

With the explosion of “Big Data” over the last few years, the need for people who know how to build and manage data-pipelines has grown.  Unfortunately, supply has not kept up with demand and there seems to be a shortage of engineers focused on…

This article was written by Emma Walker. Emma is a data scientist at Qriously.

When I started to learn about data science and consider it as a career choice, there was a diagram that I came across regularly and still come across today, in articles and even text books aimed at introducing and educating the world about the “sexiest job of the 21st century.” First created by Drew Conway, it illustrates the three broad skill groups you need to be a data scientist.…

This article was posted by Dikesh Jariwala on R Bloggers.

With ever increasing volume of data, it is impossible to tell stories without visualizations. Data visualization is an art of how to turn numbers into useful knowledge.

R Programming lets you learn this art by offering a set of inbuilt functions and libraries to build visualizations and present data. Before the…

This article was written by Nam Vu on GitHub. 

What is it? 

This is my multi-month study plan for going from mobile developer (self-taught, no CS degree) to machine learning engineer.My main goal was to find an approach to studying Machine Learning that is mainly hands-on and abstracts most of the Math for the beginner. This approach is unconventional because it’s the top-down and results-first approach designed for…

This article comes from DeepLearningPatterns.. 

Deep Learning can be described as a new machine learning toolkit that has a high likelihood to lead to more advanced forms of artificial intelligence. The evidence for this is in the sheer number of breakthroughs that had occurred since the beginning of this decade. There is a new found optimism in the air and we are now again in a new AI spring.

Unfortunately, the current state of deep learning appears to many ways to be…

Authored by Henry Gersh, with Habiba Emadi. 

Data analysis will be invaluable to any student that is considering studying Statistics at University, College or High School. The book contains both Descriptive and 1-sample Inferential Statistics and is crammed with easy to understand examples, solved problems and supplementary questions.

The book also includes 5 complete trial exams with very detailed solutions. The trial exams contain a grading system that…

This article was written by Adrian Rosebrock. Adrian is an entrepreneur and Ph.D who has launched two successful image search engines, ID My Pill and Chic Engine.…

This article was written by Saurav Kaushik. Saurav is a Data Science enthusiast, currently in the final year of his graduation at MAIT, New Delhi. He loves to use machine learning and analytics to solve complex data problems.

Introduction

Have you come across a situation when a Chief Marketing Officer of a company tells you – “Help me understand our customers better so that we can market our…

Feature engineering is essential to applied machine learning, but using domain knowledge to strengthen your predictive models can be difficult and expensive. To help fill the information gap on feature engineering, this complete hands-on guide teaches beginning-to-intermediate data scientists how to work with this…

This article was posted by Sunil Ray. Sunil is a Business Analytics and BI professional.

Source for picture: click…

This article was contributed by Nikita Johnson. 





The cost of large scale data collection and annotation often makes the application of machine learning algorithms…

This document comes from Github.

Introduction

tf-seq2seq is a general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summarization, Conversational Modeling, Image Captioning, and more.…

This article was written by Koustubh. 

Unless you have been living under the rock, you must have heard of the revolution that deep learning and convolutional neural networks have brought in computer vision. Computers have achieved near-human…

This article was written by Radhouane Aniba. 

How to pick a Data Science book :

Choosing a data science book is one of the important steps to properly learn from the experts in the field. It doesn’t have to be labeled as a data science book as it can relate to one of its…

This article comes from Toodarkpark. Below is an extract, covering a few of the programming languages listed in the original article.

The proliferation of modern programming languages (all of which seem to have stolen countless features from each other) sometimes makes it difficult to remember which language you're using. This guide is offered as a public service to help programmers in such dilemmas.…

This article was written by James Le.

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples…