Python for Data Sciences
Python has an excellent ecosystem for performing various tasks related to data sciences. Numpy, Scipy and Matplotlib provide a solid foundation for numerical operations and visualizations and they are relatively mature and well known libraries. Here, I have provided pointers to some resources on the web that I found useful in my work.
- An excellent matplotlib tutorial for plotting in Python.
- ScikitLearn is currently the most mature and well designed toolkit for doing machine learning in Python.
- TextBlob provides a simplified API for performing many common Natural Language Processing tasks.
- NetworkX is a Python library for working with Graphs.
- Seaborn is a visualization library for statistical data analysis build on top of Matplotlib. It make creating beautiful vizualization fun and easy.
- SymPy for symbolic mathematics in Python
Machine Learning
- Bayesian Method for Hackers is an online tutorial emphasizing a hands-on approach for getting started with Bayesian Analysis.
- MathematicalMonk's YouTube channel has some amazing byte-sized lessons on several topics related to Machine Learning, Information Theory and Probability