HeFlwr: Federated Learning for Heterogeneous Devices
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Updated
Jun 1, 2024 - Python
Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns.
HeFlwr: Federated Learning for Heterogeneous Devices
Curated list of Python resources for data science.
AI on Hadoop
MATLAB Project
PyTorch is an open-source machine learning library developed by Facebook's AI Research lab (FAIR). It is widely used for deep learning applications and is known for its ease of use, flexibility, and dynamic computation graph, which allows for more intuitive and flexible model building compared to static graph frameworks like TensorFlow.
This repository contains machine learning and deep learning projects from beginner to advanced, using TensorFlow and scikit-learn and other dependencices.
A neural network library built around an Automatic Differentiation system written from scratch. The main focus of this project is its 'AutoGrad' system. The overall API roughly resembles to that of PyTorch.
Machine learning and deep learning tutorials, articles and other resources. With repository stars⭐ and forks🍴
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
Visualizer for neural network, deep learning and machine learning models
TrailBlazer: Trajectory Control for Diffusion-Based Video Generation
This repository contains an implementation of a Deep Convolutional Generative Adversarial Network (DCGAN) trained on the FashionMNIST dataset. The project aims to generate realistic images of clothing items using a GAN architecture. It includes model definitions, training scripts, and visualizations of generated images at various training stages.
This project showcases a comprehensive method for predicting stock prices using an LSTM neural network. It includes fetching historical stock data, preprocessing it, building and training the LSTM model, making predictions, and visualizing outcomes. The main goal is to precisely forecast stock prices utilizing historical data.
Hello everyone this repo will contain my journey of machine learning and DeepLearning with some exciting projects
A benchmark dataset collection for bird sound classification
Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, Gemma, CLIP, ViT, ConvNeXt, BEiT, Swin Transformer, Segformer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow.
This course covers the applied side of algorithmics in machine learning and deep learning, focusing on hands-on coding experience in Python.
OpenBot leverages smartphones as brains for low-cost robots. We have designed a small electric vehicle that costs about $50 and serves as a robot body. Our software stack for Android smartphones supports advanced robotics workloads such as person following and real-time autonomous navigation.
Decentralized & federated privacy-preserving ML training, using p2p networking, in JS