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k-competitive-autoencoder-for-text

kdd2019_hetgnn

code of HetGNN

laftr

Learning Adversarially Fair and Transferable Representations

lag-fairness

learning-fair-representations

Python numba implementation of Zemel et al. 2013

learning-to-route

Code for ICML2019 paper: Learning to Route in Similarity Graphs

lstm_anomaly_thesis

Anomaly detection for temporal data using LSTMs

machine-learning-for-trading

Code for Machine Learning for Algorithmic Trading, 2nd edition.

machine-learning-project-walkthrough

An implementation of a complete machine learning solution in Python on a real-world dataset. This project is meant to demonstrate how all the steps of a machine learning pipeline come together to solve a problem!

machine-learning-with-pyspark

Source Code for 'Machine Learning with PySpark' by Pramod Singh

machine-learning-with-python

Python code for common Machine Learning Algorithms

machine-learning-with-python-1

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

ml-fairness-gym

ml_finance_codes

Machine Learning in Finance: From Theory to Practice Book

mpyc

MPyC for Secure Multiparty Computation in Python

mv-lstm

Multi-variable LSTM recurrent neural networks for prediction and interpretation of multi-variable time series

nips2017

A list of resources for all invited talks, tutorials, workshops and presentations at NIPS 2017

nlp-in-practice

Full working examples in Python with accompanying dataset for Text Mining & NLP. Includes: Gensim Word2Vec, phrase embeddings, keyword extraction with TFIDF, word count with pyspark, simple text preprocessing, accessing pre-trained embeddings and more.

nrlpapers

Must-read papers on network representation learning (NRL) / network embedding (NE)

numericaloptimization_basicalgorithm

Optimization Algorithm: convex optimization; numerical optimization

piml-toolbox

PiML (Python Interpretable Machine Learning) toolbox for model development and validation

practical-deep-learning-with-pytorch

Live Training by Packt, with Jeffrey Yau.

practical-machine-learning

Examples and code for the Practical Machine Learning workshop series

practical-ml-w-python

Source code for 'Practical Machine Learning with Python' by Dipanjan Sarkar, Raghav Bali, and Tushar Sharma

prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

pyspark-predictive-maintenance

Predictive Maintenance using Pyspark

pyspark-tutorials

Code snippets and tutorials for working with social science data in PySpark

pyspark_dist_explore

Data Exploration in PySpark made easy - Pyspark_dist_explore provides methods to get fast insights in your Spark DataFrames.

python-training

Python training for business analysts and traders

pytorch-sentiment-analysis

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.