50+ Data Science, Machine Learning Cheat Sheets, updated

This post updates a previous very popular post 50+ Data Science, Machine Learning Cheat Sheets. If we missed some popular cheat sheets, add them in the comments below. Cheatsheets on Python, R and Numpy, Scipy, Pandas Data science is a multi-disciplinary field. Thus, there are thousands of packages and hundreds of programming functions out there in the data science world! An aspiring data enthusiast need not know all. A cheat sheet or reference card is a compilation of mostly used commands to help you learn that language’s syntax at a faster rate. Here are the most important ones that have been brainstormed and captured in a few compact pages. Mastering Data science involves understanding of statistics, mathematics, programming knowledge especially in R, Python & SQL and then deploying a combination of all these to derive insights using the business understanding &…
Original Post: 50+ Data Science, Machine Learning Cheat Sheets, updated

The steps in the machine learning workflow

Previous post Next post            Tweet Tags: Machine Learning, MATLAB, Workflow We outline preprocessing steps for finding, removing, and cleaning data to prepare it for machine learning and how tools like MATLAB can help with data exploration, identification of key traits, and communicating the findings. By Seth DeLand, Product Marketing Manager, Data Analytics, MathWorks Machine learning is ubiquitous.…
Original Post: The steps in the machine learning workflow

Machine Learning Course for R&D Specialists, 4-8 April, Delft, The Netherlands

Previous post            Tweet Tags: Delft, Machine Learning, MATLAB, Netherlands, perClass Do you want to go beyond theory and learn how to create working Machine Learning solutions? This 5-day course provides you with practical step-by-step methodology. Do you want to go beyond theory and learn how to create working Machine Learning solutions? This 5-day course provides you with…
Original Post: Machine Learning Course for R&D Specialists, 4-8 April, Delft, The Netherlands

Extreme Classification Code Release

The extreme classification workshop at ICML 2015 this year was a blast. We started strong, with Manik Varma demonstrating how to run circles around other learning algorithms using a commodity laptop; and we finished strong, with Alexandru Niculescu delivering the elusive combination of statistical and computational benefit via “one-against-other-reasonable-choices” inference. Check out the entire program!Regarding upcoming events, ECML 2015 will…
Original post: Extreme Classification Code Release
Source: Machined Learnings