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gemini

Gemini is a modern LaTex beamerposter theme 🖼

geospatial-machine-learning

A curated list of resources focused on Machine Learning in Geospatial Data Science.

getspatialdata

An R package 📦 making it easy to query, preview, download and preprocess multiple kinds of spatial data 🛰 via R. All beta.

google-research

Google AI Research

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hko-7

Source code of paper "[NIPS2017] Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model"

htmresearch

Experimental algorithms. Unsupported.

individual-work

Module 2 for Campus Advisors

islr-python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

isolationforest

testing scikit-learn Isolation Forest

jmlr2018

The code of the experiments of the submitted paper "On the stability of Feature Selection" in Matlab, R and Python.

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.

kdd2019deeptcn

keras-anomaly-detection

Anomaly detection implemented in Keras

keras-tcn

Keras Temporal Convolutional Network.

lstm-anomaly-detect

Example code for neural-network-based anomaly detection of time-series data (uses LSTM)

lstm-autoencoders

Anomaly detection for streaming data using autoencoders

lstm_anomaly_thesis

Anomaly detection for temporal data using LSTMs

machine-learning-for-learning-resources

This ebook from Jason Brownlee. Educational perpose only! Thanks to Jason for the books.

machine-learning-with-python

Python code for common Machine Learning Algorithms

machine_learning_refined

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

mad-gans

Applied generative adversarial networks (GANs) to do anomaly detection for time series data

manip-ml

Code for the IEEE S&P 2018 paper 'Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning'

mathematics_for_machine_learning

This repository contains code and theory of mathematical concepts required to master Machine Learning

memae-anomaly-detection

MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.

mit-deep-learning

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

mit_ocw_linear_algebra_18_06

IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)

ml-mastery

Code from Jason Brownlee's course on mastering machine learning

ml-privacy-regulization