Search Results for "deep learning with python" - Page 14
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Showing 1757 open source projects for "deep learning with python"
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Apache Hamilton
Helps data scientists define testable self-documenting dataflows
Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. -
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Nugget
Unlock the fullest potential of your device
Nugget is a system customization toolkit designed to unlock hidden capabilities and advanced configuration options on supported devices, particularly within Apple ecosystems. It provides users with the ability to modify system-level settings that are typically restricted, such as status bar elements, lock screen behavior, and system daemons. The tool includes features for creating animated wallpapers, editing system UI elements, and enabling diagnostic or developer-oriented modes that are... -
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GPflow
Gaussian processes in TensorFlow
GPflow is a package for building Gaussian process models in Python. It implements modern Gaussian process inference for composable kernels and likelihoods. GPflow builds on TensorFlow 2.4+ and TensorFlow Probability for running computations, which allows fast execution on GPUs. -
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The Data Engineering Handbook
Links to everything you'd ever want to learn about data engineering
The Data Engineering Handbook is a comprehensive, community-curated repository that aggregates essential learning resources for anyone interested in becoming a professional data engineer. Rather than being a code project itself, it’s a learning handbook that links to books, articles, tutorials, community groups, boot camps, and real-world project examples that collectively form a roadmap to mastering data engineering skills. It includes beginner and intermediate boot camps, interview guides,... -
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marqo
Tensor search for humans
...Marqo is a versatile and robust search and analytics engine that can be integrated into any website or application. Due to horizontal scalability, Marqo provides lightning-fast query times, even with millions of documents. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. It can seamlessly handle image-to-image, image-to-text and text-to-image search and analytics. Marqo adapts and stores your data in a fully schemaless manner. It combines tensor search with a query DSL that provides efficient pre-filtering. Tensor search allows you to go beyond keyword matching and search based on the meaning of text, images and other unstructured data. ... -
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System Design Primer
Learn how to design large-scale systems
System Design Primer is a curated, open source collection of resources that helps engineers learn how to design large-scale systems. The project is structured as a comprehensive guide covering core system design concepts, trade-offs, and patterns necessary for building scalable, reliable, and maintainable systems. It offers both theoretical foundations—such as scalability principles, the CAP theorem, and consistency models—and practical exercises, including real-world system design interview... -
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stable-diffusion-videos
Create videos with Stable Diffusion
Create videos with Stable Diffusion by exploring the latent space and morphing between text prompts. Try it yourself in Colab. -
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MedicalGPT
MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training
MedicalGPT training medical GPT model with ChatGPT training pipeline, implementation of Pretraining, Supervised Finetuning, Reward Modeling and Reinforcement Learning. MedicalGPT trains large medical models, including secondary pre-training, supervised fine-tuning, reward modeling, and reinforcement learning training. -
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DI-engine
OpenDILab Decision AI Engine
DI-engine is a unified reinforcement learning (RL) platform for reproducible and scalable RL research. It offers modular pipelines for various RL algorithms, with an emphasis on production-level training and evaluation. -
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Amazon CodeGuru Profiler Python Agent
Amazon CodeGuru Profiler Python Agent
...Use CodeGuru Profiler to help profile your applications in the cloud from a single, centralized dashboard. CodeGuru Profiler currently supports applications written in all Java virtual machine (JVM) languages and Python. -
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DINOv3
Reference PyTorch implementation and models for DINOv3
DINOv3 is the third-generation iteration of Meta’s self-supervised visual representation learning framework, building upon the ideas from DINO and DINOv2. It continues the paradigm of learning strong image representations without labels using teacher–student distillation, but introduces a simplified and more scalable training recipe that performs well across datasets and architectures. DINOv3 removes the need for complex augmentations or momentum encoders, streamlining the pipeline while... -
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BudouX
Standalone, small, language-neutral
Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning-powered line break organizer tool. It is standalone. It works with no dependency on third-party word segmenters such as Google cloud natural language API. It is small. It takes only around 15 KB including its machine learning model. It's reasonable to use it even on the client-side. It is language-neutral. You can train a model for any language by feeding a dataset to BudouX’s training... -
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Nixtla TimeGPT
TimeGPT-1: production ready pre-trained Time Series Foundation Model
TimeGPT is a production ready, generative pretrained transformer for time series. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code. Whether you're a bank forecasting market trends or a startup predicting product demand, TimeGPT democratizes access to cutting-edge predictive insights, eliminating the need for a dedicated team of machine learning engineers. A generative model for time series. TimeGPT is capable of... -
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hls4ml
Machine learning on FPGAs using HLS
hls4ml is an open-source framework that enables machine learning models to be implemented directly on hardware such as FPGAs and ASICs using high-level synthesis techniques. The system converts trained neural network models from common machine learning frameworks into hardware description code suitable for ultra-low-latency inference. This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast... -
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Meta-World
Collections of robotics environments
Meta-World is an open-source benchmark suite of robotic manipulation environments focused on multi-task and meta reinforcement learning. It provides a large collection of continuous-control tasks, such as reaching, pushing, opening doors, and manipulating objects with a simulated robot arm. The library defines standardized benchmarks like MT1, MT10, and MT50 for multi-task learning, where a single policy is trained across different numbers of tasks. It also offers meta-learning benchmarks (ML1, ML10, ML45) that evaluate few-shot adaptation to new goals or entirely new tasks. ... -
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verl
Volcano Engine Reinforcement Learning for LLMs
VERL is a reinforcement-learning–oriented toolkit designed to train and align modern AI systems, from language models to decision-making agents. It brings together supervised fine-tuning, preference modeling, and online RL into one coherent training stack so teams can move from raw data to aligned policies with minimal glue code. The library focuses on scalability and efficiency, offering distributed training loops, mixed precision, and replay/buffering utilities that keep accelerators busy.... -
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spaCy models
Models for the spaCy Natural Language Processing (NLP) library
spaCy is designed to help you do real work, to build real products, or gather real insights. The library respects your time, and tries to avoid wasting it. It's easy to install, and its API is simple and productive. spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. Since its release in 2015, spaCy has become an industry... -
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TTRL
Test-Time Reinforcement Learning
TTRL is an open-source framework for test-time reinforcement learning in large language models, with a particular focus on reasoning tasks where ground-truth labels are not available during inference. The project addresses the problem of how to generate useful reward signals from unlabeled test-time data, and its central insight is that common test-time scaling practices such as majority voting can be repurposed into reward estimates for online reinforcement learning. This makes the... -
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Pedalboard
A Python library for audio
pedalboard is a Python library for working with audio: reading, writing, rendering, adding effects, and more. It supports the most popular audio file formats and a number of common audio effects out of the box and also allows the use of VST3® and Audio Unit formats for loading third-party software instruments and effects. pedalboard was built by Spotify’s Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. -
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Happy-LLM
Large Language Model Principles and Practice Tutorial from Scratch
Happy-LLM is an open-source educational project created by the Datawhale AI community that provides a structured and comprehensive tutorial for understanding and building large language models from scratch. The project guides learners through the entire conceptual and practical pipeline of modern LLM development, starting with foundational natural language processing concepts and gradually progressing to advanced architectures and training techniques. It explains the Transformer... -
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Megatron-LM
Ongoing research training transformer models at scale
Megatron-LM is a GPU-optimized deep learning framework from NVIDIA designed to train extremely large transformer-based language models efficiently at scale. The repository provides both a reference training implementation and Megatron Core, a composable library of high-performance building blocks for custom large-model pipelines. It supports advanced parallelism strategies including tensor, pipeline, data, expert, and context parallelism, enabling training across massive multi-GPU and multi-node clusters. ... -
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Antigravity Awesome Skills
The Ultimate Collection of 700+ Agentic Skills for Claude Code
Antigravity Awesome Skills is a playful yet practical repository that curates a set of clever, expressive, and sometimes whimsical AI agent skill templates designed to help users bootstrap agent behavior quickly. Rather than focusing on production-grade systems, it provides creative and high-impact skills that demonstrate how agents can be used to automate tasks, generate content, assist with daily operations, or integrate into larger workflows with minimal configuration. The project... -
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Uncertainty Baselines
High-quality implementations of standard and SOTA methods
...Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. Each baseline emphasizes reproducibility: fixed seeds, standard splits, and strong metrics such as calibration error, AUROC for OOD, and accuracy under shift. -
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Watermark Anything
Official implementation of Watermark Anything with Localized Messages
Watermark Anything (WAM) is an advanced deep learning framework for embedding and detecting localized watermarks in digital images. Developed by Facebook Research, it provides a robust, flexible system that allows users to insert one or multiple watermarks within selected image regions while maintaining visual quality and recoverability. Unlike traditional watermarking methods that rely on uniform embedding, WAM supports spatially localized watermarks, enabling targeted protection of specific image regions or objects. ... -
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Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page.
