smokarizadeh,shahab,github

2016

RecSys Challenge 2016: job recommendations

advbayeslearncourse

Course material for the PhD course Advanced Bayesian Learning at Linköping University

apm_exercises

Exercises for the book Applied Predictive Modeling by Kuhn and Johnson (2013)

bayesian-modelling-in-python

A python tutorial on bayesian modeling techniques (PyMC3)

cadl

Course materials/Homework materials for the FREE MOOC course on "Creative Applications of Deep Learning w/ Tensorflow" #CADL

catboost

CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box for Python, R

coursera-advanced-machine-learning-specialization

Repo for coursera specialization Advanced Machine Learning by Higher School of Economics

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

dat210x

Programming with Python for Data Science Microsoft

data-algorithms-book

MapReduce and Spark Source Code and Scripts for Data Algorithms Book

data-structures-algorithms-using-python

Codes for Data Structures and Algorithms Using Python, Rance D. Necaise (Wiley, 2010-12-21) Python数据结构与算法

data-structures-and-algorithms-in-python

"Data Structures and Algorithms in Python" is designed to provide an introduction to data structures and algorithms, including their design, analysis, and implementation. The authors take advantage of the beauty and simplicity of Python to present executable source code that is clear and concise. Furthermore, a consistent object-oriented viewpoint is retained throughout the book, including the use of inheritance, both to maximize code reuse and to draw attention to the clear similarities and differences of various abstract data types and algorithmic approaches.