Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

📜 🎉 Automated reporting of objects in R

Horizontal Pod Autoscaler built with predictive abilities using statistical models

Hierarchical Time Series Forecasting with a familiar API

Nyoka is a Python library that helps to export ML models into PMML (PMML 4.4.1 Standard).

A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.

Input Output Hidden Markov Model (IOHMM) in Python

Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.

Time Series Decomposition techniques and random forest algorithm on sales data

Implemented an A/B Testing solution with the help of machine learning

Udacity FWD2.0 advanced data analysis nano degree connect sessions

E-Commerce Website A/B testing: Recommend which of two landing pages to keep based on A/B testing

Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification

Material for the tutorial, "Time series analysis with pandas" at T-Academy

Here I go through the processing of prototyping a mean reversion trading strategy using statistical concepts, then test it in backtrader.

Python package for Scailable uploads