Popular GitHub Repositories for Mit Bih Arrhythmia

Instant voice cloning by MIT and MyShell. Audio foundation model.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

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

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Lab Materials for MIT 6.S191: Introduction to Deep Learning

Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.

Open Source ML Model Versioning, Metadata, and Experiment Management

Enhance Images with Javascript and AI. Increase resolution, retouch, denoise, and more. Open Source, Browser & Node Compatible, MIT License.

Một cuốn sách về Học Sâu đề cập đến nhiều framework phổ biến, được sử dụng trên 300 trường Đại học từ 55 đất nước bao gồm MIT, Stanford, Harvard, và Cambridge.

Code for training and test machine learning classifiers on MIT-BIH Arrhyhtmia database

Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.

Lab assignments for Introduction to Data-Centric AI, MIT IAP 2024 ????

slot filling, intent detection, joint training, ATIS & SNIPS datasets, the Facebook’s multilingual dataset, MIT corpus, E-commerce Shopping Assistant (ECSA) dataset, CoNLL2003 NER, ELMo, BERT, XLNet

ECG arrhythmia classification using a 2-D convolutional neural network

Starter App to Build Your Own App to Query Doc Collections with Large Language Models (LLMs) using LlamaIndex, Langchain, OpenAI and more (MIT Licensed)

MIT-Princeton Vision Toolbox for Robotic Pick-and-Place at the Amazon Robotics Challenge 2017 - Robotic Grasping and One-shot Recognition of Novel Objects with Deep Learning.

MIT-Princeton Vision Toolbox for the Amazon Picking Challenge 2016 - RGB-D ConvNet-based object segmentation and 6D object pose estimation.

ECG classification programs based on ML/DL methods