5921 Open source projects that are alternatives of or similar to Gaussianprocesses.jl

This trading-gym is the first trading for agent to train with episode of short term trading itself.

Solving NLP problems with Vowpal Wabbit: Tutorial and more

Simplified implementations of deep learning related works

書籍「つくりながら学ぶ！深層強化学習」のサポートリポジトリです

Go binding for TensorFlow Lite

Tensorflow's Fairness Evaluation and Visualization Toolkit

This is the code for the "Classifying Data using Gradient Descent" by Siraj Raval on Youtube

an numpy-based implement of PointRend

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection.

A very lightweight Python wrapper to the Philips Hue API

This is the code for "Bitcoin Prediction" by Siraj Raval on Youtube

Machine Learning Tutorials in Python

中文文本错别字检测以及自动纠错 / Autochecker & autocorrecter for chinese

Implemented digit detector in natural scene using resnet50 and Yolo-v2. I used SVHN as the training set, and implemented it using tensorflow and keras.

Survival analsyis and time-to-failure predictive modeling using Weibull distributions and Recurrent Neural Networks in Keras

A collection of tools to collect and download various data.

Deep learning infrastructure for bioinformatics

Material for the tutorial: "Deep Diving into GANs: from theory to production"

Auto-ReID and Other Person Re-Identification Projects

Python is a multi-paradigm programming language. Meaning, it supports different programming approach. One of the popular approach to solve a programming problem is by creating objects. This is known as Object-Oriented Programming (OOP).

PyTorch implementation of VQ-VAE by Aäron van den Oord et al.

This Jupyter Notebook will help you downloading Coursera videos, subtitles and quizzes (but not answering the quiz). It will automatically download and convert vtt subtitle files into srt. All resources downloaded are numbered according to their sequence.

Automatic image captioning model based on Caffe, using features from bottom-up attention.

北京邮电大学“网络搜索原理”课程资料(2019)

Some practices about deep learning

MLSS 2018 Madrid lecture materials on Generative Adversarial Networks (GANs)

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn

Progressive training of GANs with Mutual Information Penalty

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

a sklearn wrapper for Google's BERT model

Codes related to various ML Hackathons

A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook format ready to run in Google Colaboratory

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

A practical feature engineering handbook

Scripts and code examples. Includes Spark notes, Jupyter notebook examples for Spark, Impala and Oracle.

Notebooks for Course

A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

A TensorFlow implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks (http://arxiv.org/pdf/1312.6082.pdf)

InferSent sentence embeddings

scikit-learn wrappers for Python fastText.

subpixel: A subpixel convnet for super resolution with Tensorflow

Project which implements extraction of data from scatter plots

MTCNN with Motion Detection, on Raspberry Pi with Love

吴恩达机器学习coursera课程，学习代码(2017年秋) The Stanford Coursera course on MachineLearning with Andrew Ng

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code.

Previous version of eeg-notebooks

What scientific programmers must know about CPUs and RAM to write fast code.

Tutorial on "Modern Optimization Methods in Python"

Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

A crash course in six episodes for software developers who want to become machine learning practitioners.

《统计学习方法》（第一版）习题解答，在线阅读地址：https://datawhalechina.github.io/statistical-learning-method-solutions-manual

Jupyter notebooks and other materials developed for the Columbia course APMA 4300

An introduction to data science in Python, for people with no programming experience.

Materials for PyCon 2017 presentation on optimizing Pandas code

Deep Learning with TensorFlow 2 and Keras, published by Packt