An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
-
Updated
Jan 15, 2023 - HTML
An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
A collaboratively written review paper on deep learning, genomics, and precision medicine
Visualization toolkit for neural networks in PyTorch! Demo -->
The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.
18.S096 - Applications of Scientific Machine Learning
All notes and materials for the CS229: Machine Learning course by Stanford University
Machine learning and data science blog.
This repository presents a couple of approaches to the problem of multi-view image classification. I faced this challenge during a hackathon in which I participated, and decided to share my code here. I've also written a Medium article to provide further details and explanations. Feel free to check it out !
Denoising Autoencoders for Phenotype Stratification
🌈 Netron preview for VS Code (TECH DEMO!)
The goal of this project is to identify students at risk of dropping out the school
Code and simulations using biologically annotated neural networks
Supplementary materials for McLevey 2021 Doing Computational Social Science (Sage, UK).
Real-time American Sign Language (ASL) letters detection, via PyTorch, OpenCV, YOLOv5, Roboflow and LabelImg 🤟
Wildfire smoke detection with Faster R-CNN via Pytorch 🔥🚒🧑🚒
Lyra V2 (SoundStream) running in the browser
Inspired by Ilya Sutskever’s 2020 reading list to John Carmack, this repo reproduces and explores key AI papers, known as the "ilya30u30." Dive into detailed notes, code, and insights to deepen your understanding of foundational and advanced deep learning concepts.
Add a description, image, and links to the neural-networks topic page so that developers can more easily learn about it.
To associate your repository with the neural-networks topic, visit your repo's landing page and select "manage topics."