Search Results for "python (scikit-learn)"
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120 projects for "python (scikit-learn)" with 1 filter applied:
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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FastAPI Python
FastAPI framework, high performance, easy to learn, fast to code
FastAPI framework, high performance, easy to learn, fast to code, ready for production. FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based on standard Python type hints. -
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Learn AI Engineering
Learn AI and LLMs from scratch using free resources
Learn AI Engineering is a learning path for AI engineering that consolidates high-quality, free resources across the full stack: math, Python foundations, machine learning, deep learning, LLMs, agents, tooling, and deployment. Rather than a loose bookmark list, it organizes topics into a progression so learners can start from fundamentals and move toward practical, production-oriented skills. -
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Playground Cheatsheet for Python
Playground and cheatsheet for learning Python
learn-python is another repository by Oleksii Trekhleb that serves as both a playground and an interactive cheatsheet for learning Python. It contains numerous Python scripts organized by topic (lists, dictionaries, loops, functions, classes, modules, etc.), each with code examples, explanations, test assertions, and links to further readings. -
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handson-ml3
Fundamentals of Machine Learning and Deep Learning
handson-ml3 contains the Jupyter notebooks and code for the third edition of the book Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow. It guides readers through modern machine learning and deep learning workflows using Python, with examples spanning data preparation, supervised and unsupervised learning, deep neural networks, RL, and production-ready model deployment. The third edition updates the content for TensorFlow 2 and Keras, introduces new chapters (for example on reinforcement learning or generative models), and offers best-practice code that reflects current ecosystems. ... -
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mlforecast
Scalable machine learning for time series forecasting
mlforecast is a time-series forecasting framework built around machine-learning models, designed to make forecasting both efficient and scalable. It lets you apply any regressor that follows the typical scikit-learn API, for example, gradient-boosted trees or linear models, to time-series data by automating much of the messy feature engineering and data preparation. Instead of writing custom code to build lagged features, rolling statistics, and date-based predictors, mlforecast generates... -
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OpenAI Quickstart Python
Python example app from the OpenAI API quickstart tutorial
openai-quickstart-python is an official OpenAI repository containing multiple Python quickstart applications that demonstrate how to use different OpenAI API endpoints, including Chat and Assistants. It provides practical, beginner-friendly examples to help developers quickly learn how to send requests, handle responses, and build basic applications using the OpenAI Python SDK. -
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Python Zero to Hero for DevOps Engineers
Learn Python from DevOps Engineer point of you
Python Zero to Hero for DevOps Engineers is a structured “Python Zero to Hero for DevOps Engineers” course laid out as a day-by-day learning path. The repository is organized into Day-01 through Day-19 folders plus a small sample app, which makes it very easy to follow in sequence like a bootcamp. The curriculum starts with Python installation, environment setup, and writing your first script, then quickly moves into data types, strings, regular expressions, variables, and functions. It... -
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NVIDIA FLARE
NVIDIA Federated Learning Application Runtime Environment
NVIDIA Federated Learning Application Runtime Environment NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration. NVIDIA FLARE is built on a componentized architecture that allows you to take federated... -
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost... -
Level Up Your Cyber Defense with External Threat ManagementMove beyond alerts. Gain full visibility, context, and control over your external attack surface to stay ahead of every threat.
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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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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. ... -
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SuperAGI
A dev-first open source autonomous AI agent framework
An open-source autonomous AI framework to enable you to develop and deploy useful autonomous agents quickly & reliably. Join a community of developers constantly contributing to make SuperAGI better. Access your agents through a graphical user interface. Interact with agents by giving them input, permissions, etc. Agents typically learn and improve their performance over time with feedback loops. Run multiple agents simultaneously to improve efficiency and productivity. Connect to multiple... -
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CutLER
Code release for Cut and Learn for Unsupervised Object Detection
CutLER is an approach for unsupervised object detection and instance segmentation that trains detectors without human-annotated labels, and the repo also includes VideoCutLER for unsupervised video instance segmentation. The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. The codebase provides training and inference scripts, model configs, and references to... -
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TextWorld
TextWorld is a sandbox learning environment for the training
TextWorld is a learning environment designed to train reinforcement learning agents to play text-based games, where actions and observations are entirely in natural language. Developed by Microsoft Research, TextWorld focuses on language understanding, planning, and interaction in complex, narrative-driven environments. It generates games procedurally, enabling scalable testing of agents’ natural language processing and decision-making abilities. -
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Godot RL Agents
An Open Source package that allows video game creators
godot_rl_agents is a reinforcement learning integration for the Godot game engine. It allows AI agents to learn how to interact with and play Godot-based games using RL algorithms. The toolkit bridges Godot with Python-based RL libraries like Stable-Baselines3, making it possible to create complex and visually rich RL environments natively in Godot. -
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dude uncomplicated data extraction
dude uncomplicated data extraction: A simple framework
Dude is a very simple framework for writing web scrapers using Python decorators. The design, inspired by Flask, was to easily build a web scraper in just a few lines of code. Dude has an easy-to-learn syntax. Dude is currently in Pre-Alpha. Please expect breaking changes. You can run your scraper from terminal/shell/command-line by supplying URLs, the output filename of your choice and the paths to your python scripts to dude scrape command. -
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Dominate
Dominate is a Python library for creating and manipulating HTML docs
Dominate is a Python library for creating and manipulating HTML documents using an elegant DOM API. It allows you to write HTML pages in pure Python very concisely, which eliminates the need to learn another template language, and lets you take advantage of the more powerful features of Python. Dominate can also use keyword arguments to append attributes onto your tags. -
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OSWorld
Benchmarking Multimodal Agents for Open-Ended Tasks
OSWorld is an open-source synthetic world environment designed for embodied AI research and multi-agent learning. It provides a richly simulated 3D world where multiple agents can interact, perform tasks, and learn complex behaviors. OSWorld emphasizes multi-modal interaction, enabling agents to process visual, auditory, and symbolic data for grounded learning in a simulated world. -
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ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The... -
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Plugins Quickstart
Get a ChatGPT plugin up and running in under 5 minutes
plugins-quickstart is a starter project created by OpenAI to help developers build and deploy ChatGPT plugins quickly. It provides a minimal but complete example of how to structure a plugin, implement an API, and define the necessary configuration files. The repository demonstrates how a plugin can be served, authenticated, and integrated with ChatGPT for real-world use. By including both the backend code and plugin manifest, it guides developers through the end-to-end development workflow.... -
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D4RL
Collection of reference environments, offline reinforcement learning
D4RL (Datasets for Deep Data-Driven Reinforcement Learning) is a benchmark suite focused on offline reinforcement learning — i.e., learning policies from fixed datasets rather than via online interaction with the environment. It contains standardized environments, tasks and datasets (observations, actions, rewards, terminals) aimed at enabling reproducible research in offline RL. Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm... -
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Peroxide
Rust numeric library with high performance and friendly syntax
...This can make it more challenging to learn and use Rust libraries that heavily rely on Rust's unique features and syntax. -
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Courses (Anthropic)
Anthropic's educational courses
Anthropic’s courses repository is a growing collection of self-paced learning materials that teach practical AI skills using Claude and the Anthropic API. It’s organized as a sequence of hands-on courses—starting with API fundamentals and prompt engineering—so learners build capability step by step rather than in isolation. Each course mixes short readings with runnable notebooks and exercises, guiding you through concepts like model parameters, streaming, multimodal prompts, structured... -
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Flama
Fire up your models with the flame
Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. -
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Professional Programming
A collection of learning resources for curious software engineers
Professional Programming is a long-running, curated collection of learning resources aimed at helping software engineers grow into well-rounded professionals. It goes far beyond basic “learn to code” material and covers topics like system design, debugging, testing, performance, security, architecture, and software craftsmanship. The list is organized by themes such as coding, design, operations, communication, and career, making it easy to dive into specific aspects of engineering practice....
