Search Results for "scikit-learn" - Page 13
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Showing 1969 open source projects for "scikit-learn"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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NeuroMatch Academy (NMA)
NMA Computational Neuroscience course
...These videos are completely optional and do not need to be watched in a fixed order so you can pick and choose which videos will help you brush up on your knowledge. The pre-reqs refresher days are asynchronous, so you can go through the material on your own time. You will learn how to code in Python from scratch using a simple neural model, the leaky integrate-and-fire model, as a motivation. Then, you will cover linear algebra, calculus and probability & statistics. The topics covered on these days were carefully chosen based on what you need for the comp neuro course. -
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Operator Lifecycle Manager
A management framework for extending Kubernetes with Operators
This project is a component of the Operator Framework, an open source toolkit to manage Kubernetes native applications, called Operators, in an effective, automated, and scalable way. Read more in the introduction blog post and learn about practical use cases at the OLM website. OLM extends Kubernetes to provide a declarative way to install, manage, and upgrade Operators and their dependencies in a cluster. Kubernetes clusters are being kept up to date using elaborate update mechanisms today, more often automatically and in the background. Operators, being cluster extensions, should follow that. ... -
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fastn
(Alpha stage software) fastn - Full-stack Web Development Made Easy
ftd is a programming language for building user interfaces and content-centric websites. ftd is easy to learn, especially for nonprogrammers, but it does not compromise on what you can build with it. fastn is a web framework, a content management system, and an integrated development environment for ftd. fastn is a web server, that compiles ftd to HTML/CSS/JS and can be deployed on your server, or on fastn cloud by FifthTry. ftd is designed with minimal and uniform syntax, and at first glance does not even look like a programming language. -
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OpenThread
OpenThread released by Google is a thread networking protocol
OpenThread released by Google is...Thread Certified Component an open-source implementation of the Thread networking protocol. Google Nest has released OpenThread to make the technology used in Nest products more broadly available to developers to accelerate the development of products for the connected home. OS and platform agnostic, with a narrow platform abstraction layer and a small memory footprint, making it highly portable. It supports both system-on-chip (SoC) and network... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Tigo
Tigo is an HTTP web framework written in Go (Golang)
...Of course, the Tigo framework also provides developers with three toolkits, binding, logger, and request, which can be used by developers to perform structural body case studies, log records, and HTTP access requests. If you have used Tornado before, then Tigo is very easy for you to get started. Tigo provides two routing methods, and developers can learn through the right-side example. -
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Glamour
Stylesheet-based markdown rendering for your CLI apps
...You can create your own stylesheet or simply use one of the stylish defaults. You can find all available default styles in our gallery. Want to create your own style? Learn how! There are a few options for using a custom style. Call glamour.Render(inputText, "desiredStyle") Set the GLAMOUR_STYLE environment variable to your desired default style or a file location for a style and call glamour.RenderWithEnvironmentConfig(inputText). Set the GLAMOUR_STYLE environment variable and pass glamour.WithEnvironmentConfig() to your custom renderer. -
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Blockchain Guide
Introduce blockchain related technologies, from theory to practice
Blockchain is a fundamental innovation in the field of financial technology (Fintech). As the core technology of a new generation of distributed ledger technology (DLT) system, blockchain is considered to have broad application prospects in many fields such as finance, Internet of Things, commercial trade, credit reporting, and asset management. At present, blockchain technology is still in a stage of rapid development, involving distributed systems, cryptography, game theory, network... -
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Ariadne
Python library for implementing GraphQL servers
Ariadne is a Python library for implementing GraphQL servers. Schema-first. Ariadne enables Python developers to use a schema-first approach to the API implementation. This is the leading approach used by the GraphQL community and supported by dozens of frontend and backend developer tools, examples, and learning resources. Ariadne makes all of this immediately available to you and other members of your team. Ariadne offers a small, consistent, and easy to memorize API that lets developers... -
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EpicReact.Dev
Build a ReactJS App workshop
...A guided workflow, driven by a node go script and INSTRUCTIONS.md, lets learners move between exercises and extra credit steps while the repository updates the working files for each stage. Extensive tests, using Jest in watch mode, help students verify their solutions and learn how to work with test-driven feedback. -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Bend
A massively parallel, high-level programming language
Bend is an interactive programming environment (REPL) built on top of the Kotlin language, designed to allow users to explore, experiment, and learn Kotlin in a live, feedback-driven manner. The tool lets you define variables, functions, or values at the prompt and iteratively refine them—immediately seeing output and types—while preserving state across commands. It emphasizes discoverability and experimentation: users can inspect functions, call them on sample inputs, and evolve logic without a full project scaffold. ... -
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Datasets
Hub of ready-to-use datasets for ML models
Datasets is a library for easily accessing and sharing datasets, and evaluation metrics for Natural Language Processing (NLP), computer vision, and audio tasks. Load a dataset in a single line of code, and use our powerful data processing methods to quickly get your dataset ready for training in a deep learning model. Backed by the Apache Arrow format, process large datasets with zero-copy reads without any memory constraints for optimal speed and efficiency. We also feature a deep... -
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AWS Load Balancer Controller
A Kubernetes controller for Elastic Load Balancers
...This project was formerly known as "AWS ALB Ingress Controller", we rebranded it to be "AWS Load Balancer Controller". AWS ALB Ingress Controller was originated by Ticketmaster and CoreOS as part of Ticketmaster's move to AWS and CoreOS Tectonic. Learn more about Ticketmaster's Kubernetes initiative from Justin Dean's video at Tectonic Summit. AWS ALB Ingress Controller was donated to Kubernetes SIG-AWS to allow AWS, CoreOS, Ticketmaster and other SIG-AWS contributors to officially maintain the project. The controller watches for ingress events from the API server. When it finds ingress resources that satisfy its requirements, it begins the creation of AWS resources. -
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Theseus
A library for differentiable nonlinear optimization
...Theseus bridges the gap between classical optimization and deep learning, enabling hybrid systems that learn components. -
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WrenAI
Open-source SQL AI Agent for Text-to-SQL. Make Text2SQL Easy
...Wren AI has implemented a semantic engine architecture to provide the LLM context of your business; you can easily establish a logical presentation layer on your data schema that helps LLM learn more about your business context. With Wren AI, you can process metadata, schema, terminology, data relationships, and the logic behind calculations and aggregations with “Modeling Definition Language”, to generate accurate SQL queries with semantic context. When starting a new conversation in Wren AI, your question is used to find the most relevant tables. ... -
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Better Stack JavaScript client
Better Stack JavaScript client
...See what metrics your teammates are looking at, comment on note-worthy data spikes and share log fragments with one click. Building a great software is a multiplayer game. Get answers fast with a powerful SQL query builder. No need to learn a new querying language or ask your data analyst. -
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Zingg
Scalable master data management and identity resolution
Zingg is an open-source entity resolution and master data management platform for finding duplicate, related, or matching records across large datasets. It uses machine learning to learn how records should be compared, reducing the need for brittle hand-written matching rules. The project is designed for data engineering and analytics teams working on customer 360, supplier 360, deduplication, fuzzy matching, data quality, and golden record workflows. Zingg runs on Apache Spark and can scale to large data lake, warehouse, and cloud platform environments. ... -
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anti-distill
Anti-distillation for employee Skills
anti-distill is a research-oriented project focused on protecting machine learning models from knowledge distillation attacks, where smaller models attempt to replicate the behavior of larger proprietary systems. The project explores techniques that make it harder for external models to learn from outputs, thereby preserving intellectual property and model uniqueness. It likely introduces methods such as output perturbation, watermarking, or response shaping to prevent accurate imitation. The system is particularly relevant in contexts where models are exposed via APIs and risk being reverse-engineered through repeated querying. ... -
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Companion notebooks for Deep Learning
Jupyter notebooks for the code samples of the book
...The project covers a wide range of topics, including neural networks, computer vision, natural language processing, and sequence modeling. Each notebook is structured to combine theoretical explanations with executable code, allowing users to experiment and learn interactively. The material is designed to be accessible while still covering advanced topics, making it suitable for both beginners and intermediate practitioners. It leverages modern libraries and frameworks to demonstrate real-world applications of deep learning techniques. The notebooks also emphasize best practices in model training, evaluation, and deployment. ... -
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VoxelMorph
Unsupervised Learning for Image Registration
...Traditional image registration techniques typically rely on optimization procedures that must be executed separately for each pair of images, which can be computationally expensive and slow. VoxelMorph approaches the problem using neural networks that learn to predict deformation fields that transform one image so that it aligns with another. Once the model has been trained, it can rapidly compute the transformation required to register new image pairs, significantly reducing computational time compared to classical registration algorithms. The framework supports both supervised and unsupervised learning approaches and is commonly used in medical imaging applications such as MRI alignment, anatomical analysis, and longitudinal studies. -
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Kodezi Chronos
Kodezi Chronos is a debugging-first language model
...The project introduces architectural techniques such as Adaptive Graph-Guided Retrieval, which allows the system to navigate large repositories and retrieve relevant debugging information from multiple sources. Another component, Persistent Debug Memory, allows the system to learn patterns from past debugging sessions and apply that knowledge to future problems. The repository mainly contains research documentation, evaluation benchmarks, and experimental frameworks rather than the full proprietary model implementation. -
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learning
A log of things I'm learning
...The content is organized into categories that cover both core engineering skills and adjacent technologies, enabling readers to follow a practical roadmap for developing strong technical foundations. The repository emphasizes clear explanations, curated resources, and concise notes designed to help developers learn complex topics efficiently. Because it is updated regularly, it reflects evolving trends in software engineering and emerging technologies such as modern AI systems. -
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Super comprehensive deep learning notes
Super Comprehensive Deep Learning Notes
Super comprehensive deep learning notes is a massive and well-structured collection of deep learning notebooks that serve as a comprehensive study resource for anyone wanting to learn or reinforce concepts in computer vision, natural language processing, deep learning architectures, and even large-model agents. The repository contains hundreds of Jupyter notebooks that are richly annotated and organized by topic, progressing from basic Python and PyTorch fundamentals to advanced neural network designs like ResNet, transformers, and object detection algorithms. ... -
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Personal AI Infrastructure
Agentic AI Infrastructure for magnifying HUMAN capabilities
...Unlike once-stateless chatbots, this platform captures context, memory, goals, preferences, and feedback to enable an AI that understands you and improves over time, using a full agentic stack rather than simple question-answer loops. PAI blends tools like browsing, code editing, execution, and more into a continuous Observe → Think → Plan → Execute → Verify → Learn cycle, letting the system refine its behavior with each use. Its architecture supports long-term memory, verification of actions, and ongoing self-improvement, blurring the line between “assistant” and persistent, evolving collaborator. -
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LatentMAS
Latent Collaboration in Multi-Agent Systems
LatentMAS is an advanced framework for multi-agent reinforcement learning (MARL) that uses latent variable modeling to bridge perception and decision-making in environments where agents must coordinate under uncertainty. It provides mechanisms for agents to learn high-level latent representations of states, which simplifies complex sensory inputs into compact, actionable embeddings that facilitate both individual policy learning and inter-agent coordination. Using this latent space, the framework enables Multi-Agent Systems (MAS) to scale more effectively in environments with high dimensionality — such as robotics, simulated physics tasks, and strategic games — by reducing redundant learning burdens and focusing agent exploration. ... -
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Motor
The async Python driver for MongoDB and Tornado or asyncio
...Built on top of Python’s Tornado and asyncio frameworks, Motor lets you issue database operations without blocking the event loop, enabling concurrency in web servers, real-time systems, and microservices. It provides a familiar API surface similar to the official synchronous PyMongo driver, so you can migrate or write MongoDB code in Python without having to learn a completely new interface. Because it integrates with popular async ecosystems like FastAPI, Sanic, and aiohttp, Motor is a natural fit for modern async Python stacks where throughput and responsiveness matter. It also supports change streams, grid file system (GridFS), and the full range of CRUD and aggregation operations available in MongoDB.
