Deep Learning Book Chinese Translation
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
The most cited deep learning papers
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
DeepFaceLab is the leading software for creating deepfakes.
The best design tools and plugins for everything
Books for machine learning, deep learning, math, NLP, CV, RL, etc
A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance, NeurIPS 2020 DRL workshop.
This is a deep learning based robot which follows a person in dynamic environment.
DeepFaceLab is the leading software for creating deepfakes.
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.
Human activity recognition, or HAR, is a challenging time series classification task. It involves predicting the movement of a person based on sensor data and traditionally involves deep domain expertise and methods from signal processing to correctly engineer features from the raw data in order to fit a machine learning model.
Visualizer for neural network, deep learning, and machine learning models
A Deep-Learning Chess Engine with some awesome features
Machine Learning and Deep Learning lessons.
Natural language processing (NLP) is an exciting branch of artificial intelligence (AI) that allows machines to break down and understand human language. I plan to walk through text pre-processing techniques, machine learning techniques and Python libraries for NLP. Text pre-processing techniques include tokenization, text normalization and data cleaning. Once in a standard format, various machine learning techniques can be applied to better understand the data. This includes using popular modeling techniques to classify emails as spam or not, or to score the sentiment of a tweet on Twitter. Newer, more complex techniques can also be used such as topic modeling, word embeddings or text generation with deep learning. We will walk through an example in Jupyter Notebook that goes through all of the steps of a text analysis project, using several NLP libraries in Python including NLTK, TextBlob, spaCy and gensim along with the standard machine learning libraries including pandas and scikit-learn.
Developed using Pybullet, OpenCV and Deep Learning
This project contains codes for solving complex problems with Spark. It also shows extension of new libraries and API with Spark such as Deep Learning with Spark, Geo-spatial analytics with Spark etc
Repository dedicated to Deep Learning Course took at the Federal University of Paraíba, Brazil
Tensorflow based implementation of various deep learning applcations.
Introduction to Deep Reinforcement Learning
Example deep learning projects that use wandb's features.
Determined: Deep Learning Training Platform
Autonomously learning to race autonomously
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Model Zoo for Intel Architecture: contains Intel optimizations for running deep learning workloads on Intel Xeon Scalable processors
CLI tool to build, test, debug, and deploy Serverless applications using AWS SAM
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai
A convenient starting template and pipeline for most deep learning projects. Built with PyTorch Lightning and Weights&Biases
A procedural Blender pipeline for photorealistic training image generation
A pre-trained deep learning system for detecting bird flight calls in continuous recordings
Device Information for React Native iOS and Android
A small library for managing deep learning models, hyperparameters and datasets
.NET Stream Processing Library for Apache Kafka
An API-first distributed deployment system of deep learning models using timeseries data to analyze and predict systems behaviour
A high-level machine learning and deep learning library for the PHP language.
Deep learning based prediction of pi-helices in protein sequences
AutoML library for deep learning
Deep Learning Very High performance operations written to run on GPU supporting CUDA.
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