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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
TensorFlow Model Optimization is a toolkit designed to optimize machine learning models for deployment for Keras and TensorFlow. It includes techniques such as quantization and pruning to reduce model size and improve inference performance.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Flexible, high-performance serving system for machine learning models.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
A web app to generate template code for machine learning.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Weights & Biases is an open-source AI developer platform. It is used to train and fine-tune machine learning models, and manage models across the full lifecycle from experimentation to production. The associated wandb library is hosted in a public GitHub repository.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Gold is a reinforcement learning library for Go. It provides a set of agents for solving challenges in various environments, with composable tooling for creating agents and visualizing their performance. Agents include Q Learning, Deep Q learning with Double Q, REINFORCE, Natural Evolution Strategies, Hindsight Experience Replay and Proximal Policy Optimization, which is marked in progress.
github.com
Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].
github.com
Repository of machine-checkable security models for Clawdbot, written primarily in TLA+ and checked with TLC. It functions as a security regression suite in which green models should pass and deliberately buggy red models should fail with a counterexample trace. Some checks are conformance-style, validating that the formal model matches Clawdbot's implementation constants.
github.com
Ray is an AI compute engine consisting of a core distributed runtime and AI libraries for scaling AI and Python applications. It runs on any machine, cluster, cloud provider, and Kubernetes, and is installed with pip install ray.
github.com
Open-source runtime for numerical computing that executes MATLAB-syntax code. Built in Rust, it provides a compiler, a virtual machine, and JIT tiers, with a GPU backend powered by wgpu. The project targets CPU and GPU hardware and handles tensor allocations and movement automatically.
github.com
AI Expert Roadmap presents a set of charts showing paths and technologies for becoming a data scientist, machine learning or AI expert. An interactive version with links is available online, and the project is published under the MIT license.