Tutorials

Python

Pycrumbs – an awesome collection of python tutorials and how-tos. Bookmark it!
Getting Started with Python: Tips, Tools and Resources – a very organized list of resources to start learning Python.
Learn X in Y minutes: Python – Goes over the basic constructs of Python using a single piece of code. Pretty good for beginners.
Learning Python – this interactive tutorial for absolute beginners will get you quickly started with Python.

R

Quick introduction to ggplot2 – very nice and easy explanation on plotting using R
R Cookbook (O’Reilly) – anyone doing data analysis using R must have this book for quick recipes.

Tools for Data Analysis – pandas, matplotlib, scipy, numpy

Getting Started with Python for Data Science – good tutorial to quickly get your python environment setup for diving into data science with python.
Python and Pandas – a good tutorial for beginners starting with data analysis using pandas. It illustrates, as the blogger calls it, the top 10 features of pandas.
Matplotlib Tutorial – a basic tutorial on using matplotlib for your plotting needs
Multiple plots in a single figure – this stackoverflow answer is very simple to understand and illustrates all the basics.
Playing with numpy arrays – for people looking to learn about slicing, sorting, filtering etc. with np arrays, here’s a good start
ggplot for python – Perfect for people who love ggplot in R. Now its in python!!

Data Science

Data Science 101 – a good blog covering various topics on data science

Machine Learning

Intuitive classification using KNN and Python – a good article explaining the concept of KNN and illustrates an example in Python for easy understanding

Mathematics

Math and Programming Primers – Great blog for learning several math concepts. Good set of primers given by the blogger.

Statistics

Tutorial on Sampling Theory (applied to databases) – this post contains some basics of sampling theory which can be applied to any field of focus (and not limited to the context in which the blogger has presented it). The explanation is more theoretical than intuitive but nevertheless helpful.

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