6792 Open source projects that are alternatives of or similar to Enet Real Time Semantic Segmentation

Movie plots by genre tutorial at PyData Berlin 2016

Hierarchical Attention Networks for Chinese Sentiment Classification

List of tech resources future me and other Javascript/Ruby/Python/Elixir/Elm developers might find useful

Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019

VQVAEs, GumbelSoftmaxes and friends

Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5

メディカルAIコース オンライン講義資料

Learn OpenCV : C++ and Python Examples

Self hosted alternative to Google Photos

A Deep Learning based project for colorizing and restoring old images (and video!)

Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)

Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832

Seed, Expand, Constrain: Three Principles for Weakly-Supervised Image Segmentation

Pytorch version of Realtime Multi-Person Pose Estimation project

This is the code for "Predicting the Winning Team with Machine Learning" by Siraj Raval on Youtube

Code for the paper "Evolved Policy Gradients"

Natural Language Processing with TensorFlow, published by Packt

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

Beautiful charting of pandas.DataFrame with Highcharts

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

The Bukkit/Spigot/Paper API implementation for Fabric

A collection of Jupyter Notebooks for learning Python for Data Science.

Contains files related to content and project of DSND

emoji2vec: Learning Emoji Representations from their Description

Repository containing files for my PyCon 2014 scikit-learn tutorial.

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

Code for the paper "Language Models are Unsupervised Multitask Learners"

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

Machine Learning for finance and investment introduction

Scientific Python Geometric Algorithms Library

Ten Simple Rules for Writing and Sharing Computational Analyses in Jupyter Notebooks

Generating multiple choice questions from text using Machine Learning.

Real Time Big Data / IoT Machine Learning (Model Training and Inference) with HiveMQ (MQTT), TensorFlow IO and Apache Kafka - no additional data store like S3, HDFS or Spark required

A tutorial on TensorFlow

Dense Depth for Autonomous Driving (DDAD) dataset.

source{d} datasets ("big code") for source code analysis and machine learning on source code

These are my learning exercices from Coursera

A web frontend for scheduling Jupyter notebook reports

A benchmark dataset for data-driven weather forecasting

Summaries of machine learning papers

AI 算法岗简历模板

Respository for Open-Science modular microscope system.

AI residency programs information

Train and Deploy Simple Machine Learning Model With Web Interface - Docker, PyTorch & Flask

fastai V2 implementation of Timeseries classification papers.

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

The open-source tool for building high-quality datasets and computer vision models

A Python package for exploring and analysing genetic variation data

A simple but complete full-attention transformer with a set of promising experimental features from various papers

Materials for an online-course - "Practical XGBoost in Python"

TensorFlow Tutorials

💎 数学公式识别

A collection of all my datasets

A knowledge graph and a set of tools for drug repurposing

add statistical annotations (pvalue significance) on an existing boxplot generated by seaborn boxplot

A collection of various deep learning architectures, models, and tips

Data Visualization with Python

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.