Directory
Published directory entries matching your search.
A PyTorch implementation of the DeepDream algorithm hosted on GitHub. The repository provides code for running the DeepDream algorithm using the PyTorch framework, with support for features including specific channel selection and activation strength-based channel selection.
A parallel deep learning framework hosted on GitHub. The project provides a framework for building and running deep learning workflows with parallel processing support, and includes documentation for setup, available layers, and dependencies.
PaddlePaddle is an open-source parallel distributed deep learning framework developed from industrial practice, designed for high-performance single-machine and distributed training, as well as cross-platform deployment of deep learning and machine learning models.
Polyaxon is a platform for building, training, and monitoring large-scale deep learning applications. It deploys into any data center or cloud provider and supports major deep learning frameworks such as Tensorflow, MXNet, Caffe, and Torch. It manages workloads with container and node management and offers hyperparameter tuning through experiment groups defining a search algorithm and search space.
PyTorch is a Python package providing tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. It includes components such as torch, torch.autograd, torch.nn, and torch.utils, and can be used as a NumPy replacement or a deep learning research platform.
r/DeepSeek points to a Reddit community or thread with discussion, updates, troubleshooting, or shared resources.
An article by Cavin on Deep Markets discussing machine-generated content and creativity. It describes technology as leverage over creation: writing, the printing press, the internet, digital tools and machine learning. It also covers synthetic text from large language models such as OpenAI's GPT-3, published in summer 2020.
A library created for PyTorch users to launch, train, and use PyTorch models on almost any device and distributed configuration. It abstracts the boilerplate code related to multi-GPUs, TPUs, and fp16 while leaving the rest of the code unchanged, and supports automatic mixed precision and FSDP and DeepSpeed.
Apache MXNet is a deep learning framework mixing symbolic and imperative programming. It includes a dynamic dependency scheduler that parallelizes symbolic and imperative operations, with a graph optimization layer for symbolic execution. The repository was archived on Nov 17, 2023, and is read-only.
AutoKeras is an AutoML library for deep learning built on Keras, developed by DATA Lab at Texas A&M University. The project describes its goal as making machine learning accessible to everyone. It can be installed with pip, and the documentation states it is currently only compatible with Python 3.7 or later and TensorFlow 2.8.0 or later.
Awesome AutoDL is a curated list of automated deep learning resources and an in-depth analysis, subtitled that neural architecture search is not the end. It collects papers, libraries and benchmarks covering neural architecture search and hyper-parameter optimization.
List of awesome compiler projects and papers for tensor computation and deep learning.
Theano based library for deep and recurrent neural networks.
burn is a next-generation tensor library and deep learning framework developed by tracel-ai. It is designed to prioritize flexibility, efficiency, and portability, with available resources covering use with Rust, its ecosystem, supported backends, and training and inference functionality.
Caffe is a deep learning framework developed by Berkeley AI Research and community contributors, designed with expression, speed, and modularity in mind. It is released under the BSD 2-Clause license and includes associated reference models.
Catniff is a small deep learning framework for JavaScript built to be Torch-like and inspired by Tinygrad APIs. It is under development, and its APIs can be unstable and backwards-incompatible. It provides tensors, autograd and optimizers, and is installed through npm.
Chain of Thought is a podcast hosted by Conor Bronsdon about AI and software infrastructure, featuring conversations with people building AI agents and infrastructure. Guests include people from NVIDIA, Google DeepMind, AMD, Databricks and Vercel. The show has 78 episodes and is available on YouTube, Spotify, Apple Podcasts and RSS.
A PyTorch based deep learning library for drug pair scoring.
Cogitare is a modern, fast, modular deep learning and machine learning framework for Python built on top of PyTorch, with a user-friendly interface for beginners and advanced toolsets for experts.
This is a fast C++/CUDA implementation of convolutional [DEEP LEARNING].
A Neural Network Playground is a browser-based educational visualization created by Daniel Smilkov and Shan Carter for experimenting with a real neural network. Users adjust controls to explore how a network learns from data. The project is open sourced on GitHub under the Apache License so its features can be tailored to a topic or lesson.
An agentic LLM for autonomous data science that performs data preparation, analysis, modeling, visualization, and report generation without human intervention. It supports open-ended research on structured, semi-structured, and unstructured data sources, and the model, code, training data, and demo are open-sourced.
DeepDetect is a deep learning runtime, command-line tool and REST server for training and inference. It provides Python wheel variants for CPU and GPU environments and a command-line interface with profiles such as object detection and semantic segmentation. YAML configuration files make runs repeatable. It handles images, text, tabular data, time series, object-detection boxes and segmentation masks through a single API surface.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
