ab-be

ab-be.github.io

Build a Jekyll blog in minutes, without touching the command line.

BatchRenormalization

Batch Renormalization algorithm implementation in Keras

catboost

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

ctr-criteo

kaggle 2014 criteo ctr竞赛方案整理 https://www.kaggle.com/c/criteo-display-ad-challenge

Deep-and-Cross-Keras

Keras Implementation for "Deep & Cross Network for Ad Click Predictions"

deep-belief-network

A Python implementation of Deep Belief Networks built upon NumPy and TensorFlow with scikit-learn compatibility

Deep-Learning-Boot-Camp

A community run, 5-day PyTorch Deep Learning Bootcamp

fastText

Library for fast text representation and classification.

Flask-GoogleMaps

Easy way to add GoogleMaps to Flask applications.

Kaggle

Kaggle-Competition-Favorita

5th place solution for Kaggle competition Favorita Grocery Sales Forecasting

kaggle-web-traffic

1st place solution

kaggle-youtube-porto

keras

Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.

keras-attention-mechanism

Attention mechanism Implementation for Keras.

LightGBM

A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.

mlcrate

A python module of handy tools and functions, mainly for ML and Kaggle

Multicore-TSNE

Parallel t-SNE implementation with Python and Torch wrappers.

neuralnilm

Deep Neural Networks Applied to Energy Disaggregation

predictor_stacker

Linear Predictor Stacker aims at optimizing predictor's weights against a ML metric

PyPDF2

A utility to read and write PDFs with Python

python-ffm

Python Wrapped LibFFM

scikit-learn

scikit-learn: machine learning in Python

seq2seq-signal-prediction

Signal prediction with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow

smc_electricity_forecast

Projet ENSAE - Modèles à chaîne de Markov cachée et méthodes de Monte Carlo séquentielles - Antoine Grelety, Samir Tanfous, Zakarya Ali

turicreate

Turi Create simplifies the development of custom machine learning models.

web-traffic-forecasting

Kaggle | Web Traffic Forecasting 📈

Wordbatch

Parallel text feature extraction for machine learning

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow

yle-uutiset

Yle Uutiset Applications