Captum is an open-source library for PyTorch that provides tools for model interpretability. It supports multi-modal models across vision and text, allowing users to understand…
Best AI Tools for Machine Learning Engineers
529 toolsDiscover the best AI tools for Machine Learning Engineers — from AI agent observability and computer vision platforms to AI models, frameworks, and data management solutions, this is where machine learning professionals find resources that streamline complex tasks: developing robust AI models, deploying scalable applications, monitoring agent performance, and managing large datasets efficiently. Browse 529 AI Tools for Machine Learning Engineers across AI Apps, AI Models, AI Frameworks, AI Platforms and AI GitHub Repos and more.
529 tools
Rerun is the data layer for physical AI, providing primitives to build, understand, and improve your data loop. It handles multi-rate, multimodal data from initial recording to…
AI Apps
Riku.AI is a no-code platform for building, testing, and deploying AI applications. Create chat, text, image, and vision apps in minutes using over 40 world-class LLMs. Integrate…
AI Apps
Pangeanic empowers enterprises, AI labs, and governments to build multilingual AI systems. They provide trusted datasets, human feedback for model alignment, secure language…
AI Apps
Grably provides high-quality, multi-modal human interaction and conversational datasets for AI research. They capture and structure physical motion, physiological signals, gaze,…
AI Platforms
Wallaroo.ai is an AI platform that provides tools for deploying, managing, and monitoring machine learning models. It aims to simplify the MLOps lifecycle, enabling teams to bring…
AI Platforms
NVIDIA provides a comprehensive AI platform powering advancements in artificial intelligence, high-performance computing, gaming, and autonomous systems. Their solutions enable…
AI Platforms
Paperspace, now part of DigitalOcean, offers an MLOps platform for building and scaling AI applications. It provides integrated tools like Notebooks, Machines, and Deployments,…
AI Platforms
Seldon Core is an MLOps and LLMOps framework for deploying, managing, and scaling AI systems on Kubernetes. It enables standardized deployment of various model types across…
AI Platforms
Cortex provides scalable cloud infrastructure for deploying, managing, and scaling machine learning models in production. It offers serverless and batch processing, automated…
AI Platforms
KServe is an open-source, Kubernetes-native platform for self-hosted AI inference. It offers a unified solution for both generative and predictive AI, simplifying deployments from…
AI Platforms
Graphcore develops specialized processors designed to accelerate machine learning and AI applications. Their technology empowers innovators to create breakthroughs in artificial…
AI Platforms
Tenstorrent is a computing company developing next-generation hardware and software for AI. They offer AI workstations, servers, and flexible IP solutions. Their open-source…
AI Platforms
Blaize offers an AI Services Platform delivering AI applications as APIs, enabling rapid deployment of business outcomes. Their edge AI platforms, Pathfinder and Xplorer, provide…
AI Platforms
SUPERWISE AMP is an Agentic Management Platform for regulated industries, offering complete visibility, real-time guardrails, and policy enforcement. It enables businesses to…
AI Platforms
DKube empowers enterprises to deploy secure, production-ready private AI systems. It enables building AI solutions across on-prem and hybrid environments, ensuring full control,…
AI Platforms
NVIDIA NeMo provides synthetic data generation tools to accelerate agentic AI development. It creates high-quality, domain-specific datasets for training and evaluating AI models,…
AI Platforms
Imagimob specializes in Edge AI and tinyML, providing solutions for deploying machine learning on edge devices. Their DEEPCRAFT™ Studio accelerates AI model development, while…
AI Platforms
DVC is an open-source version control system for data science and machine learning projects. It provides a Git-like experience to manage data, models, and experiments, bringing…
AI Platforms
DataRobot Product Documentation provides comprehensive resources for its end-to-end AI platform. Access detailed guides, tutorials, and API documentation for both code-first and…
AI Platforms
Databricks Feature Store is a central registry for AI/ML features within Unity Catalog. It offers built-in governance, lineage, point-in-time joins, and online serving for…
This is a fine-tuned version of Llama 2 13b, enhanced with additional attention heads from Llama 33b. It was trained on approximately 10 million tokens from RedPajama to better…
AI Models
DETR is an end-to-end object detection and panoptic segmentation framework that integrates Transformers as a core component. It simplifies the architecture, directly predicts…
AI Models
Densenet is a deep convolutional neural network architecture available through PyTorch. It enhances feature propagation and reuse by connecting each layer to every other layer in…
MobileNets are a family of mobile-first computer vision models for TensorFlow, designed for efficient on-device or embedded applications. They maximize accuracy while minimizing…
AI Models
SqueezeNet is a deep convolutional neural network model available through PyTorch. It achieves AlexNet-level accuracy with significantly fewer parameters and a smaller model size,…
AI Models
Xception is a deep learning model available through the Keras 3 API. It is part of Keras Applications, offering pre-trained models for various computer vision tasks. Xception is…
AI Models
Transfo-XL-WT103 is a causal transformer model with relative positioning embeddings that can reuse hidden states for longer context. Developed by Zihang Dai and others, it uses…
AI Models
Google DeepMind explores large language models like Gopher, focusing on their capabilities, ethical considerations, and efficient training. Research includes a 280 billion…
AI Models
This research empirically analyzes the optimal trade-off between model size and training data for large language models given a fixed compute budget. It reveals that current large…
AI Models
FaceNet is a TensorFlow implementation for face recognition and clustering, based on the FaceNet paper. It leverages deep learning models to generate unified embeddings for faces,…
AI Models
Longformer Base 4096 is a transformer model designed for processing long documents. It builds upon RoBERTa, pretrained on extended sequences up to 4,096 tokens. This model employs…
AI Models
The BigBird base model is a transformer that extends BERT to handle much longer sequences using block sparse attention. It is pre-trained on English text for masked language…
AI Models
Phi-2 is a 2.7 billion-parameter language model from Microsoft Research. It demonstrates outstanding reasoning and language understanding, achieving state-of-the-art performance…
AI Models
This AI model details a large, deep convolutional neural network trained for ImageNet classification. It achieved state-of-the-art results with top-1 and top-5 error rates of…
AI Models
This GitHub repository provides an example implementation of Deep Convolutional Generative Adversarial Networks (DCGAN) using PyTorch. It allows users to train models on datasets…
AI Models
UL2 20B is an open-source unified language learner model that unifies various language modeling paradigms. It improves performance across fine-tuning and few-shot learning tasks…
This framework introduces a novel active learning method for enriching large 3D shape datasets with semantic region annotations. It efficiently combines manual annotation,…
AI Models
DGCNN is an AI model for learning on point clouds, implementing Dynamic Graph CNN. It achieves state-of-the-art performance in tasks like classification and segmentation of 3D…
AI Models
MMAction2 is a foundational library for action recognition and video understanding tasks. It provides a comprehensive toolkit for developing and deploying state-of-the-art video…
AI Models
AudioLM is an AI model that generates high-quality audio with long-term consistency. It treats audio generation as a language modeling task, mapping audio to discrete tokens. The…
ALIGN is an AI model that scales visual and vision-language representation learning using noisy text supervision from over one billion image-alt-text pairs. It achieves…
AI Models
BEiT is a self-supervised vision representation model that uses masked image modeling to pre-train vision transformers. It tokenizes images into visual tokens and recovers masked…
AI Models
Variational autoencoders (VAEs) offer a probabilistic approach to latent space representation. Unlike standard autoencoders, VAEs encode observations into probability…
AI Models
Reformer is an AI model that enhances the Transformer architecture for processing extensive sequential data. It addresses limitations in attention mechanisms and memory…
AI Models
Mamba is a novel state space model architecture designed for efficient sequence modeling, particularly effective on information-dense data like language. It offers a…
AI Models
RWKV is a powerful language model that offers efficient inference and flexible fine-tuning capabilities. It supports various applications, including desktop GUIs, web-based…
AI Models
OpenELM is a state-of-the-art open language model family from Apple Machine Learning Research. It features a layer-wise scaling strategy for enhanced accuracy and provides a…
AI Models
零一万物 (01.AI) is a global AI company focused on AI 2.0, driven by foundation model breakthroughs. They aim to revolutionize technology, platforms, and applications, creating a new…
AI Models
Octo is an open-source, generalist robot policy designed for broad applicability in robotic manipulation. This transformer-based diffusion policy is pretrained on a large dataset,…
AI Models
Fast R-CNN is a deep learning framework for object detection. It significantly speeds up training and testing compared to previous methods like R-CNN and SPPnet, achieving higher…
AI Models
py-faster-rcnn is a Python implementation of the Faster R-CNN object detection model. It offers an alternative to the official MATLAB version, providing similar accuracy with…
AI Models
Caffe framework with SSD implementation for object detection. This repository provides a fast, open framework for deep learning, specifically tailored for the Single Shot MultiBox…
AI Models
Feature Pyramid Networks (FPN) enhance object detection by creating multi-scale feature maps from deep convolutional networks with minimal computational overhead. This…
AI Models
DeepLab is a state-of-the-art deep learning model for semantic image segmentation. This TensorFlow implementation provides code for training, evaluation, and visualization of…
AI Models
ViT-Adapter is an AI model that enhances Vision Transformer (ViT) performance for dense prediction tasks like object detection and segmentation. It introduces image-specific…
AI Models
TimeSformer is a novel AI architecture for video understanding, exclusively utilizing self-attention Transformers. It achieves state-of-the-art results on action recognition…
AI Models
This AI model offers a general-purpose solution for image-to-image translation tasks. It learns both the image mapping and the appropriate loss function, enabling versatile…
AI Models
DM-GAN is a PyTorch implementation of Dynamic Memory Generative Adversarial Networks for text-to-image synthesis. This repository provides code, pretrained models, and evaluation…
AI Models
Imagen Video is a text-conditional video generation system developed by Google Research. It leverages a cascade of video diffusion models to create high-definition videos from…
AI Models
This AI model introduces a novel neural network architecture, the RNN Encoder-Decoder, for statistical machine translation. It uses two recurrent neural networks to encode source…
AI Models
ULMFiT is a powerful technique for fine-tuning pre-trained language models. It enables efficient transfer learning for text classification tasks, achieving state-of-the-art…
AI Models
Together AI is a platform for AI models. It provides access to various models, enabling developers to integrate advanced AI capabilities into their applications. The platform…
AI Models
GIT (Generative Image-to-text Transformer) is an AI model by Microsoft for vision and language tasks. It generates text descriptions from images and can perform visual question…
AI Models
Dreamer V3 is a general reinforcement learning algorithm that learns environment models to solve diverse control tasks. It excels across over 150 tasks with a single…
AI Models
This repository provides the author's official PyTorch implementation of Twin Delayed Deep Deterministic Policy Gradients (TD3). It is designed for continuous control tasks within…
AI Models
This repository provides an implementation of Principal Neighbourhood Aggregation (PNA) for Graph Neural Networks. It supports PyTorch, DGL, and PyTorch Geometric frameworks,…
AI Models
This GitHub repository provides PyTorch implementations for DeepGCNs, DeeperGCN, and GNN1000. It enables training very deep Graph Convolutional Networks by adapting concepts from…
AI Models
FastSpeech 2 is an end-to-end text-to-speech model that enhances voice quality and training speed. It directly incorporates speech variation information like pitch and energy,…
AI Models
HiFi-GAN is a generative adversarial network for efficient and high-fidelity speech synthesis. It models periodic patterns in audio to enhance sample quality, achieving human-like…
AI Models
ESPnet is an open-source toolkit for end-to-end speech processing. It provides comprehensive recipes and tools for tasks like Automatic Speech Recognition (ASR), Text-to-Speech…
AI Models
MUSE is a Python library for creating multilingual word embeddings, supporting both unsupervised and supervised methods. It aligns fastText embeddings into a common space and…
AI Frameworks
LIBSVM is an integrated software package for support vector classification, regression, and distribution estimation. It offers a user-friendly interface, supports multi-class…
AI Models
The Vision Transformer (ViT) repository provides models and code for image recognition tasks. It includes implementations of the Vision Transformer and MLP-Mixer architectures,…
AI Models
FNet is an efficient Transformer-like encoder architecture that replaces self-attention with Fourier Transforms. Developed by Google Research, it offers a high-performance…
AI Models
SpanBERT is an AI model focused on improving pre-training by representing and predicting spans. It offers pre-trained base and large cased models, compatible with HuggingFace BERT…
AI Models
LayoutLM is a multimodal pre-training model for visually-rich document understanding and information extraction. It combines text, layout, and image information to achieve…
AI Models
UniLM is a large-scale, self-supervised pre-training framework developed by Microsoft. It enables models to learn across diverse tasks, languages, and modalities, including text,…
AI Models
MASS is a pre-training method for sequence-to-sequence language generation tasks. It masks sentence fragments for the encoder to predict in the decoder, enhancing tasks like…
AI Models
PEGASUS is a state-of-the-art abstractive text summarization model developed by Google Research. It utilizes a novel pre-training objective, gap-sentence generation, to achieve…
AI Models
ProphetNet is a research project by the MSRA NLC team focused on natural language generation. It provides official implementations of pretrained models, including those for future…
AI Models
DeBERTa is a large-scale pre-trained language model developed by Microsoft Research. It surpasses T5 11B models in performance and achieves human-level results on SuperGLUE…
AI Models
Funnel-Transformer is an AI model that compresses hidden states to reduce computation cost. It allows for deeper or wider models with the same FLOPs and can recover token-level…
AI Models
ConvBERT is an open-source AI model for pre-training language models, introducing a novel architecture with span-based dynamic convolution. This GitHub repository provides the…
AI Models
MPNet is a novel pre-training method for language understanding tasks, improving upon BERT and XLNet. It offers a unified implementation for various pre-training models and…
AI Models
node2vec is a scalable framework for learning continuous feature representations of nodes in graphs. It optimizes neighborhood preservation through biased random walks, enabling…
This repository provides the official code implementation for the research paper "How Attentive are Graph Attention Networks?" published at ICLR'2022. It offers reproducible…
AI Models
SEAL is a novel framework for link prediction that transforms the problem into a subgraph classification task. It extracts h-hop enclosing subgraphs and node information matrices,…
AI Models
GraphSAINT is a flexible framework for training deep Graph Neural Networks (GNNs) on large graphs. It introduces a novel minibatch training method using graph sampling, offering…
AI Models
RoboCat is a self-improving AI agent for robotics that learns to perform diverse tasks across different robotic arms. It can adapt to new tasks with as few as 100 demonstrations…
AI Models
StyleSwin is a transformer-based Generative Adversarial Network (GAN) designed for high-resolution image generation. It leverages Swin transformers and a novel double attention…
AI Models
This AI model introduces a multiresolution hash encoding for neural graphics primitives, enabling near-instant training of neural networks on a single GPU. It significantly…
AI Models
GET3D is a generative AI model that synthesizes high-quality 3D textured meshes directly from 2D image collections. It generates diverse shapes with complex topology and rich…
AI Models
Decision Transformer reframes reinforcement learning as a sequence modeling problem, leveraging Transformer architectures like GPT-x and BERT. It generates optimal actions by…
AI Models
PyTorch implementation of the TabNet paper, offering an attentive and interpretable approach to tabular data learning. It supports classification, regression, and multi-task…
AI Models
Neural Oblivious Decision Ensembles (NODE) is a Python library for deep learning on tabular data. It implements ensembles of oblivious, differentiable decision trees, offering a…
This GitHub repository provides the official implementation for the NeurIPS 2021 paper 'Revisiting Deep Learning Models for Tabular Data.' It explores deep learning architectures…
AI Models
This repository provides the official PyTorch implementation of the SAINT model, designed for improved neural networks on tabular data. It leverages row attention and contrastive…
AI Models
R-FCN is a region-based object detection framework that utilizes fully convolutional networks for accurate and efficient image analysis. It shares computation across the entire…
AI Models
SPP_net is a re-implementation of the Spatial Pyramid Pooling algorithm for deep convolutional networks in visual recognition. It aims to reproduce object detection results from a…
AI Models
Squeeze-and-Excitation Networks (SENet) is a deep learning model architecture that adaptively recalibrates channel-wise feature responses. It enhances performance by explicitly…
AI Models
The ShuffleNet Series repository offers a collection of highly efficient convolutional neural network models designed for mobile devices and resource-constrained environments. It…
AI Models
MnasNet automates the design of mobile machine learning models by incorporating speed constraints directly into the search reward function. This platform-aware approach identifies…
AI Models
This repository provides an implementation of ConvMixer, a convolutional neural network architecture for image recognition tasks. It is based on the paper "Patches Are All You…
AI Models
RepVGG is a powerful and simple ConvNet architecture that achieves high accuracy on ImageNet. It utilizes a VGG-style design with re-parameterization techniques, allowing for…
AI Models
MobileOne is an efficient neural network backbone designed for mobile devices. It optimizes for inference speed, achieving under 1 ms on an iPhone12 with high accuracy. This model…
AI Models
Vision GNN (ViG) is a PyTorch implementation of Vision Graph Neural Networks developed by Huawei Noah's Ark Lab. It offers efficient AI backbones for image processing tasks,…
AI Models
Deformable Convolutional Networks (DCN) enhance deep learning models by adaptively learning sampling offsets for convolutional kernels. This allows networks to better capture…
AI Models
PointPillars for KITTI object detection is a GitHub repository providing code to reproduce results from the PointPillars paper on the KITTI dataset. It's a fork of the SECOND…
AI Models
SECOND PyTorch is an open-source implementation of the SECOND object detection network for KITTI and NuScenes datasets. It utilizes sparse convolutions for efficient 3D object…
AI Models
Panoptic FPN unifies instance and semantic segmentation into a single network architecture. It enhances Mask R-CNN with a semantic segmentation branch using a shared Feature…
AI Models
Skip-Thought Vectors provides Sent2Vec encoder and training code based on the research paper "Skip-Thought Vectors." It enables the generation of dense vector representations for…
AI Models
InferSent is a sentence embedding method that generates semantic representations for English sentences. Trained on natural language inference data, it generalizes well to various…
AI Models
CTRL is a 1.6 billion-parameter conditional transformer language model for controllable text generation. It conditions on control codes to specify domain, entities, and…
AI Models
The BAAI Models platform offers a diverse collection of AI models for natural language processing, multimodal understanding, and protein analysis. Explore and download models for…
AI Models
DialoGPT is a large-scale pretrained language model for dialogue response generation. Developed by Microsoft, it leverages GPT-2 architecture and is trained on extensive Reddit…
AI Models
Meena is a 2.6 billion parameter neural conversational model designed for open-domain dialogue. It aims to provide more sensible and specific responses than existing chatbots,…
AI Models
GODEL is a large-scale pre-trained Transformer-based model for goal-directed dialog generation. It excels at response generation grounded in external text, enabling efficient…
AI Models
RETRO (Retrieval Enhanced Transformers) is an AI model that augments transformer architectures with retrieval capabilities. It accesses a vast database of text passages, including…
AI Models
BERT offers two multilingual models: Cased and Uncased, supporting over 100 languages. The Cased model is recommended for non-Latin alphabets and general use, while the Uncased…
AI Models
This repository provides a TensorFlow implementation of the BEGAN (Boundary Equilibrium Generative Adversarial Networks) model. It allows users to train and test generative models…
AI Models
LS-GAN, or Loss-Sensitive Generative Adversarial Networks, is a project focused on advancing GANs. It introduces a novel approach to loss functions, aiming for improved generation…
AI Models
This repository provides a PyTorch implementation of MADE (Masked Autoencoder Density Estimation). It enables turning auto-encoders into autoregressive density models by masking…
AI Models
StyleGAN-XL is an AI model for generating high-resolution images from large, diverse datasets. It scales StyleGAN architecture for improved image synthesis quality and diversity.…
AI Models
StyleGAN3 is a generative adversarial network that eliminates "texture sticking" by overhauling signal processing. It achieves translation and rotation equivariance, enabling more…
AI Models
SoundStorm is an AI model for efficient, non-autoregressive audio generation. It produces high-quality audio two orders of magnitude faster than previous methods, maintaining…
AI Models
AlphaStar is an AI model that achieved Grandmaster level in StarCraft II, a complex real-time strategy game. It utilizes multi-agent reinforcement learning and imitation learning,…
AI Models
Policy gradient methods are a class of reinforcement learning algorithms that directly learn a policy function. Unlike value-based methods, they optimize a policy's parameters to…
AI Models
SARSA is a reinforcement learning algorithm for learning Markov decision process policies. It updates Q-values based on the agent's current state, action, reward, next state, and…
AI Models
Q-learning is a model-free reinforcement learning algorithm that trains an agent to assign values to actions based on current states. It optimizes decision-making by maximizing…
This project provides a Keras-based implementation of Relational Graph Convolutional Networks (R-GCNs). It is designed for semi-supervised node classification on directed…
AI Models
CompGCN is a PyTorch implementation of Composition-Based Multi-Relational Graph Convolutional Networks. It enables advanced graph representation learning for tasks like knowledge…
AI Models
This repository provides a PyTorch implementation of the "Simple and Deep Graph Convolutional Networks" (GCNII) model. It includes code for replicating semi-supervised and…
AI Models
This GitHub repository provides TensorFlow and PyTorch implementations for the PPNP and APPNP models, introduced in the "Predict then Propagate: Graph Neural Networks meet…
This repository provides the official implementation for the "Simplifying Graph Convolutional Networks" paper. It offers a streamlined Graph Convolutional Network (GCN) model that…
AI Models
Graph Neural PDEs is an open-source project providing Python code for Graph Neural Networks (GNNs) that treat graph learning as a continuous diffusion process. It implements GRAND…
AI Models
This blog post introduces a new PyTorch Hopfield layer based on modern Hopfield Networks. It generalizes classical Hopfield Networks to continuous states and patterns, offering…
AI Models
A self-organizing map (SOM) is an unsupervised machine learning technique that reduces data dimensionality while preserving topological structure. It creates a low-dimensional…
AI Models
A radial basis function network is an artificial neural network utilizing radial basis functions as activation functions. It's adept at function approximation, time series…
AI Models
A Bayesian network is a probabilistic graphical model representing variables and their conditional dependencies using a directed acyclic graph. It's ideal for predicting the…
AI Models
Markov Random Fields (MRFs) are undirected graphical models representing probabilistic relationships between random variables. They are crucial in AI for modeling dependencies in…
AI Models
OpenSpiel is a comprehensive framework for reinforcement learning research in games. It offers a collection of environments and algorithms for developing and testing general AI…
AI Models
SAGPool is an official PyTorch implementation of Self-Attention Graph Pooling, presented at ICML 2019. This read-only, archived repository provides the code for a novel graph…
Scikit-learn's semi-supervised learning module enables models to leverage unlabeled data alongside labeled data for improved generalization. It offers algorithms like Self…
AI Models
Temporal Graph Networks (TGNs) offer a generic, efficient framework for deep learning on dynamic graphs. This Python-based library utilizes novel memory modules and graph-based…
AI Models
EvolveGCN provides code for Evolving Graph Convolutional Networks designed for dynamic graphs. This AI model, published in AAAI 2020, offers a framework for analyzing and modeling…
AI Models
xDeepFM is an open-source deep learning toolkit for factorization models, specifically releasing the source code for the eXtreme Deep Factorization Machine (xDeepFM) model. It…
AI Models
This GitHub repository provides a TensorFlow implementation of the Attentional Factorization Machine (AFM) model. It allows users to train and evaluate AFM for tasks like…
AI Models
TensorFlow Models is a GitHub repository offering a collection of models and examples built with TensorFlow. It serves as a central hub for developers to access, contribute to,…
AI Models
LightGCN is a simplified Graph Convolutional Network designed for recommendation systems. It focuses on the essential neighborhood aggregation component for collaborative…
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