joaquinvanschoren Goto Github PK

anomaly_detection_dl

Implementation of Deep Generative Models for Anomaly Detection

awesome-seml

A curated list of articles that cover the software engineering best practices for building machine learning applications.

bdt4pa

Materials for a talk in the workshop on Big Data Tools for Physics and Astronomy

benelearn2017

book

book

build_and_test_examples

Examples of build scripts and unit test frameworks for various languages, and how these can be used with the Jenkins continuous integration server. Contact: @mikej888

building-machine-learning-systems-with-python-third-edition

Code repository for Building Machine Learning Systems with Python Third Edition, by Packt

coms4995-s18

COMS W4995 Applied Machine Learning - Spring 18

data-analysis-and-machine-learning-projects

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

data-readiness.github.io

Repo to store suggestions about data readiness levels.

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

databrewer-recipes

DataBrewer Recipes Repository.

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

fastpages

An easy to use blogging platform, with enhanced support for Jupyter Notebooks.

frugalml

Codes for the study of Machine learning algorithms on wearable devices

gama

An automated machine learning tool based on genetic programming.

gprs15b

Gaussian Process Summer School, Melbourne, Australia, 20015

home

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"

jads_dm

Materials for the JADS course data mining (introductory, 1st year bachelor)

joaquinvanschoren.github.io

jupyter-book

Create beautiful, publication-quality books and documents from computational content.

learndatascience

Open Content for self-directed learning in data science

liac-arff

A library for read and write ARFF files in Python

m-clark.github.io

machine_learning

Python coded examples and documentation of machine learning algorithms.

material-ui

Material-UI is a simple and customizable component library to build faster, beautiful, and more accessible React applications. Follow your own design system, or start with Material Design.

meta-learn.github.io

metafeatures

Meta-feature extractor

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville