This article comes from Deep Learning Patterns. 

Note to reader: Diving into this material here can be a bit overwhelming. One way though to get an understanding of the thought process is to follow the…

This article was published by Andre De Castro on Blockgeeks. Andre is the CEO & Co-Founder of Blockchain of Things, Inc. 

Blockchain has become a media buzz due to its unique and powerful qualities. While a lot of excitement exists for its use in both financial and identity applications, a new and more exciting area for this technology has emerged. It is …

This article was written by Monica Rogati. Monica is an independent data science executive and advisor. She built key data products and teams at Jawbone and LinkedIn; she now helps companies make the most out of their data.

Do a project you care about. Make it good and share it.

There’s a lot of interest in becoming a data scientist, and for good reasons: high impact, high job satisfaction, high salaries,…

This article was posted by Sunil Ray. Sunil is a Business Analytics and Intelligence professional with deep experience in the Indian Insurance industry.

Introduction

Linear and Logistic regressions are usually the first algorithms people learn in predictive modeling. Due to their popularity, a lot of analysts even end up thinking that they are the only form of regressions. The ones who are slightly more involved think that they…

This article was posted by Roberto Rösler on his personal blog about R and data mining. Roberto is a data scientist working at a major telecommunication company in Germany.…

This article was written by Adam Geitgey. Adam is interested in computers and machine learning. He likes to write about it. 

This article was written by Jean Francois Puget. 

What programming language should one learn to get a machine learning or data science job?  That's the silver bullet question.  It is debated in many forums.  I could provide here my own answer to it and explain why, but I'd rather look at some…

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…