11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals)
Are you a MIS/Reporting/BI professional trying to get into data science? Here is a comprehensive article listing down 11 steps you should follow!
Improve Your Model Performance using Cross Validation (in Python and R)
Learn various methods of cross validation including k fold to improve the model performance by high prediction accuracy and reduced variance
15 Trending Data Science GitHub Repositories you can not miss in 2017
Introduction GitHub is much more than a software versioning tool, which it was originally meant to be. Now people from different backgrounds and not …
Understanding Support Vector Machine algorithm from examples (along with code)
Note: This article was originally published on Oct 6th, 2015 and updated on Sept 13th, 2017 Overview Explanation of support vector machine (SVM), a …
6 Easy Steps to Learn Naive Bayes Algorithm with codes in Python and R
Note: This article was originally published on Sep 13th, 2015 and updated on Sept 11th, 2017 Overview Understand one of the most popular and …
Commonly used Machine Learning Algorithms (with Python and R Codes)
Note: This article was originally published on August 10, 2015 and updated on Sept 9th, 2017 Overview Major focus on commonly used machine learning …
30 Questions to test a data scientist on K-Nearest Neighbors (kNN) Algorithm
Introduction If you were to ask me 2 most intuitive algorithms in machine learning – it would be k-Nearest Neighbours (kNN) and tree based …
CatBoost: A machine learning library to handle categorical (CAT) data automatically
Introduction How many of you have seen this error while building your machine learning models using “sklearn”? I bet most of us! At least in …
Understanding and coding Neural Networks From Scratch in Python and R
Overview Neural Networks are one of the most popular machine learning algorithms Gradient Descent forms the basis of Neural networks Neural networks can be …
22 must watch talks on Python for Deep Learning, Machine Learning & Data Science (from PyData 2017, Amsterdam)
Introduction Python is increasingly gaining popularity among machine learning and data science communities across the world – and for the right reasons. It probably …
