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imbalanced-learn

Python module to perform under sampling and over sampling with various techniques.

instacart-basket-prediction

Kaggle: Instacart Market Basket Analysis, 3rd Place

instacart-basket-prediction-1

RNNs (and other stuff) for Kaggle's Instacart order prediction competition

interactive-gp-visualization

Interactive visualization of Gaussian processes

interpret

Fit interpretable models. Explain blackbox machine learning.

introduction-to-julia

Learn the language basics in this 10-part course.

ios-nbukit

UIKit and NSFoundation convenience categories and subclasses.

iot-distancemeter

Transmit sonic sensor data using RaspberryPi/Logstash/MQTT/Python

ipython-notebooks

A collection of IPython notebooks covering various topics.

jekyll-text-theme

💎 🐳 A super customizable Jekyll theme for personal site, team site, blog, project, documentation, etc.

jlrs

Julia bindings for Rust

jodie

A PyTorch implementation of ACM SIGKDD 2019 paper "Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks"

juliaconworkshop21

kafka-streams-machine-learning-examples

This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, DeepLearning4 and other technologies.

kaggle-blackbox

Deep learning made easy

kaggle-driver-telematics

AXA Driver Telematics Challenge on Kaggle.com

kaggle-seeclickfix-ensemble

Prize winning solution to the SeeClickFix contest hosted on Kaggle, developed by teammates Bryan Gregory and Miroslaw Horbal. The purpose of the contest was to train a model (as scored by RMSLE) using supervised learning that will accurately predict the views, votes, and comments that an issue posted to the www.seeclickfix.com website will receive. My teammate and I used this ensemble code base to combine our top ranked individual models to create a prize-winning solution, defeating >500 other teams and winning a prize of $1,000.

kaggle-seeclickfix-model

Prize-winning solution for Kaggle contest "SeeClickPredictFix". The purpose of the contest was to train a model (as scored by RMSLE) using supervised learning that will accurately predict the views, votes, and comments that an issue posted to the www.seeclickfix.com website will receive. This code developed by me uses a segment based ensemble to generate predictions for the 3 targets (views, votes, and comments). My teammate and I used this model in combination with his to create a winning model for the contest, defeating >500 other teams and winning a purse of $1,0000.

kaggle-toxic-starter

Extensible starter code for the Kaggle competition:

kaggle_see_click_fix

Linear model for 2nd place submission of Kaggle's See Click Predict Fix competition

kajiya

💡 Experimental real-time global illumination renderer 🦀

kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

kdd2013authorpaperidentification

Benchmark and sample code for the Author Paper Identification Challenge on Kaggle, a part of the 2013 KDD Cup

kendryte-ide

Kendeyte IDE ✨

keras

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

keras-flask-deploy-webapp

:smiley_cat: Pretty&simple image classifier app template. Deploy your own trained model or pre-trained model (VGG, ResNet, Densenet) to a web app using Flask in 10 minutes.

keras-gp

Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.

keras-retinanet

Keras implementation of RetinaNet object detection.

kindelia

A minimal decentralized computer.

lda

Topic modeling with latent Dirichlet allocation using Gibbs sampling