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kaggle-allstate

Allstate Purchase Prediction Challenge on Kaggle

kaggle-bike-sharing

An implementation of a conditional inference tree model in R for the Kaggle.com Bike Sharing Demand challenge.

kagglesberbanhouseprice

Kaggle competition for house price prediction

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

learndatascience

Open Content for self-directed learning in data science

machine-learning-coursera

Lecture notes and assignments for coursera machine learning class

ml-challenge-1

This repository contains winners code of challenge.

mlapp

Solutions to exercises from Machine Learning: A Probabilistic Perspective by Kevin P. Murphy

mlatgraddays

Course of Machine Learning in Science and Industry at Heidelberg university

mlatimperial2017

Materials for the course of machine learning at Imperial College organized by Yandex SDA

mleap

MLeap allows for easily putting Spark ML pipelines into production

mlss

Machine Learning Summer School

osaka_prml_reading

大阪PRML読書会のためのリポジトリです。

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

profiletrimming

projects

Personal Projects

pyprobml

Python code for "Machine learning: a probabilistic perspective"

pythondatasciencehandbook

Jupyter Notebooks for the Python Data Science Handbook

reddit-churn-prediction

revrand

A library of scalable Bayesian generalised linear models with fancy features

scipy-lecture-notes

Notes used to give tutorials at Euroscipy conference

spark-ml-class

Coursera Machine Learning class examples in Spark

spark-py-notebooks

Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

spark-workshop

A free tutorial for Apache Spark.

statistical-rethinking

Solutions for the practice problems

text-analytics-with-python

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress (part of Springer Science+Business Media).

thinkbayes

Jupyter Notebooks derived from Allen Downey's book Think Bayes.

thinkbayes2

Text and code for the second edition of Think Bayes, by Allen Downey.

training-classifier-in-python

Using Python to build a classifier with different algorithm (KNN, NB, SVM, Neural Networks)

uofwashington-machinelearning

Coursera:Univ of Washington:Machine Learning