Search Results for "reasoning machine learning" - Page 16
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Showing 858 open source projects for "reasoning machine learning"
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Pytorch-toolbelt
PyTorch extensions for fast R&D prototyping and Kaggle farming
A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses:... -
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SAHI
A lightweight vision library for performing large object detection
A lightweight vision library for performing large-scale object detection & instance segmentation. Object detection and instance segmentation are by far the most important fields of applications in Computer Vision. However, detection of small objects and inference on large images are still major issues in practical usage. Here comes the SAHI to help developers overcome these real-world problems with many vision utilities. Detection of small objects and objects far away in the scene is a major... -
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PySyft
Data science on data without acquiring a copy
Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data... -
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Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase,... -
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NLP
Open source NLP guide with models, methods, and real use cases
...NLP extends into real-world applications, including sentiment analysis and text classification, helping readers connect concepts to use cases. Designed for accessibility, the project evolves over time, allowing updates and improvements as NLP techniques advance. It reflects a practical approach to learning, where readers can explore code, experiment with models, and build foundational skills in machine learning-driven language processing. -
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SafeClaw
Chat with it via text and voice
SafeClaw is an open-source, entirely local alternative to cloud-based AI assistants like OpenClaw, enabling users to build a personal assistant that runs on their own machine without incurring API usage charges or exposing data to third-party services. It emphasizes privacy and predictability by using traditional programming, rule-based intent parsing, and established machine learning tools rather than large language models, meaning there are no per-token API costs and deterministic behavior. The assistant offers features such as voice control using fully local speech-to-text (Whisper) and text-to-speech (Piper) capabilities, news aggregation with extractive summarization, and smart home or Bluetooth device control. ... -
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Tencent-Hunyuan-Large
Open-source large language model family from Tencent Hunyuan
Tencent-Hunyuan-Large is the flagship open-source large language model family from Tencent Hunyuan, offering both pre-trained and instruct (fine-tuned) variants. It is designed with long-context capabilities, quantization support, and high performance on benchmarks across general reasoning, mathematics, language understanding, and Chinese / multilingual tasks. It aims to provide competitive capability with efficient deployment and inference. FP8 quantization support to reduce memory usage... -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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LightAutoML
Fast and customizable framework for automatic ML model creation
LightAutoML is an automated machine learning (AutoML) framework optimized for efficient model training and hyperparameter tuning, focusing on both tabular and text data. -
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tiny-llm
A course of learning LLM inference serving on Apple Silicon
...The project is structured as a guided course that walks developers through the process of implementing the core components required to run a modern language model, including attention mechanisms, token generation, and optimization techniques. Rather than relying on high-level machine learning frameworks, the codebase uses mostly low-level array and matrix manipulation APIs so that developers can understand exactly how model inference works internally. The project demonstrates how to load and run models such as Qwen-style architectures while progressively implementing performance improvements like KV caching, request batching, and optimized attention mechanisms. ... -
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TextAttack
Python framework for adversarial attacks, and data augmentation
Generating adversarial examples for NLP models. TextAttack is a Python framework for adversarial attacks, data augmentation, and model training in NLP. -
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Cleanlab
The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. ... -
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Qwen3 Embedding
Designed for text embedding and ranking tasks
Qwen3-Embedding is a model series from the Qwen family designed specifically for text embedding and ranking tasks. It builds upon the Qwen3 base/dense models and offers several sizes (0.6B, 4B, 8B parameters), for both embedding and reranking, with high multilingual capability, long‐context understanding, and reasoning. It achieves state-of-the-art performance on benchmarks like MTEB (Multilingual Text Embedding Benchmark) and supports instruction-aware embedding (i.e. embedding task... -
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Robyn
Experimental, AI/ML-powered and open sourced Marketing Mix Modeling
Robyn is an open-source, AI/ML-powered Marketing Mix Modeling (MMM) toolkit developed by Meta Marketing Science under the “facebookexperimental” GitHub umbrella. Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of... -
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MindsDB
Making Enterprise Data Intelligent and Responsive for AI
MindsDB is an AI data solution that enables humans, AI, agents, and applications to query data in natural language and SQL, and get highly accurate answers across disparate data sources and types. MindsDB connects to diverse data sources and applications, and unifies petabyte-scale structured and unstructured data. Powered by an industry-first cognitive engine that can operate anywhere (on-prem, VPC, serverless), it empowers both humans and AI with highly informed decision-making... -
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Director
AI video agents framework for next-gen video interactions
Director is a video database management system designed to organize, search, and retrieve large collections of video content efficiently. -
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TensorFlow Hub
A library for transfer learning by reusing parts of TensorFlow models
...These models can be loaded directly into TensorFlow pipelines and fine-tuned for new tasks using transfer learning techniques. The repository supports contributions from the community, allowing developers to submit models that become available for use by other machine learning practitioners. By enabling reusable model modules, TensorFlow Hub significantly reduces development time and computational cost when building machine learning systems. -
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MaxText
A simple, performant and scalable Jax LLM
...MaxText includes ready-to-use configurations and reproducible training examples that help developers understand how to deploy large-scale AI workloads with modern machine learning infrastructure. -
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Colab-MCP
An MCP server for interacting with Google Colab
...Instead of relying on manual notebook usage, the system allows MCP-compatible agents to execute code, manage files, install dependencies, and orchestrate entire development workflows within Colab’s cloud infrastructure. This approach bridges the gap between local AI agents and remote high-performance compute environments, allowing users to offload heavy workloads such as machine learning training, data analysis, and dependency-heavy tasks to Colab’s GPU and TPU resources. By exposing Colab as an MCP server, the tool enables seamless integration with a wide range of AI assistants and agent frameworks, creating a standardized interface for tool use and execution. -
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Freqtrade
Free, open source crypto trading bot
...It is designed to support all major exchanges and be controlled via Telegram or WebUI. It contains backtesting, plotting, and money management tools as well as strategy optimization by machine learning. Always start by running a trading bot in Dry-run and do not engage money before you understand how it works and what profit/loss you should expect. We strongly recommend you have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms, and techniques implemented in it. ... -
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ModelScope
Bring the notion of Model-as-a-Service to life
ModelScope is built upon the notion of “Model-as-a-Service” (MaaS). It seeks to bring together most advanced machine learning models from the AI community, and streamlines the process of leveraging AI models in real-world applications. The core ModelScope library open-sourced in this repository provides the interfaces and implementations that allow developers to perform model inference, training and evaluation. In particular, with rich layers of API abstraction, the ModelScope library offers unified experience to explore state-of-the-art models spanning across domains such as CV, NLP, Speech, Multi-Modality, and Scientific-computation. ... -
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Hermes Agent
The agent that grows with you
Hermes Agent is a fully open-source autonomous AI agent designed to run persistently on your own machine or server, becoming more capable the longer it operates by learning from experience and building reusable procedural skills. Rather than functioning as a stateless chatbot, it maintains long-term memory across sessions and can generate searchable “Skill Documents” that capture how it solved complex tasks so it doesn’t start from scratch each time. -
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PyTextRank
Python implementation of TextRank algorithms
PyTextRank is a Python implementation of TextRank as a spaCy pipeline extension, for graph-based natural language work -- and related knowledge graph practices. -
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Cybergod
A program that can do anything to earn money without human operators
AGI Computer Control is an experimental autonomous software system designed to operate independently and generate income without human intervention. It aims to simulate artificial general intelligence (AGI) by leveraging evolutionary algorithms, deep active inference, and other advanced AI techniques. The project explores the boundaries of machine autonomy and self-directed behavior in computational environments.
