deep-learning

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Deep Learning toolkit for Computer Vision.

Graph Neural Networks with Keras and Tensorflow 2.

Curated List of Self-Driving Cars and Autonomous Vehicles Resources

Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. This is part of the CASL project: http://casl-project.ai/

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

Open Source Neural Machine Translation in Torch (deprecated)

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Vietnamese TTS with instant voice cloning • On-device • Real-time CPU inference • 24kHz audio quality • Chuyển văn bản thành giọng nói tiếng Việt • Text to speech tiếng Việt • TTS tiếng Việt

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

An Extensible Deep Learning Library

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)

The Natural Language Decathlon: A Multitask Challenge for NLP

Run Mixtral-8x7B models in Colab or consumer desktops

Source-to-Source Debuggable Derivatives in Pure Python

🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱

:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling