Search Results for "python (scikit-learn)" - Page 3
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Showing 95 open source projects for "python (scikit-learn)"
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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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Flask-SQLAlchemy
Adds SQLAlchemy support to Flask
Flask-SQLAlchemy is an extension for Flask that adds support for SQLAlchemy to your application. It simplifies using SQLAlchemy with Flask by setting up common objects and patterns for using those objects, such as a session tied to each web request, models, and engines. Flask-SQLAlchemy does not change how SQLAlchemy works or is used. See the SQLAlchemy documentation to learn how to work with the ORM in depth. The documentation here will only cover setting up the extension, not how to use... -
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ComfyUI Experiments
Some experimental custom nodes
ComfyUI_experiments is a playground repo for trying out new, sometimes unstable ideas in the ComfyUI ecosystem before they graduate into more official nodes or workflows. It’s where experimental nodes, pipelines, or integrations can live without breaking users’ main installations. The project is aimed at power users and contributors who want to see “what’s possible” with ComfyUI beyond the stable set of features. Because it is exploratory, the code may change often, rely on specific... -
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KAGSA
KAGSA PROGRAMMING LANGUAGE
it designed to be easy to learn and practical for use in various projects. It has a flexible syntax and allows some things that other languages prohibit, such as using certain symbols in variable names and starting variable names with numbers. KAGSA contains several main components, including a lexer, syntax checker, parser, and compiler. It supports object-oriented programming, iteration, and other features commonly used in programming languages. -
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UnionML
Build and deploy machine learning microservices
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
Reinforcement-learning is a widely used educational repository that provides implementations, exercises, and solutions for a broad range of reinforcement learning algorithms, designed to complement foundational texts and courses in the field. The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so... -
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Gym
Toolkit for developing and comparing reinforcement learning algorithms
Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no... -
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SageMaker Scikit-Learn Extension
A library of additional estimators and SageMaker tools based on scikit
A library of additional estimators and SageMaker tools based on scikit-learn. This project contains standalone scikit-learn estimators and additional tools to support SageMaker Autopilot. Many of the additional estimators are based on existing scikit-learn estimators. SageMaker Scikit-Learn Extension is a Python module for machine learning built on top of scikit-learn. In order to use the I/O functionalies in the sagemaker_sklearn_extension.externals module, you will also need to install the mlio version 0.7 package via conda. ... -
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Awesome Conformal Prediction
A professionally curated list of awesome Conformal Prediction videos
awesome-conformal-prediction is a curated “awesome list” repository on GitHub collecting high-quality resources related to conformal prediction: tutorials, books, papers, theses, open-source libraries, videos, and other educational material. It is not a software library itself but a directory of resources for those wanting to learn or work with conformal prediction and uncertainty quantification. This exceptional resource is the culmination of my PhD journey in Machine Learning, specializing... -
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Raiden Network
Raiden Network
Use Raiden to enrich your dApp with nearly instant, low-fee and scalable payments. It comes with an easy-to-use API and is compatible with the Ethereum ERC20 token standard. Incentivized, decentralized P2P live streaming with micropayments using Raiden, introducing “Proof-of-Stream-Payment”. The Raiden Network is an infrastructure layer on top of the Ethereum Blockchain. While the basic idea is simple, the underlying protocol is quite complex and the implementation non-trivial. Nonetheless... -
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YOLOR
implementation of paper - You Only Learn One Representation
YOLOR is the implementation of “You Only Learn One Representation,” a unified network approach for learning explicit and implicit knowledge together. The project focuses on object detection while exploring how a shared representation can support multiple tasks. It builds on the YOLO family and related PyTorch detection work, combining practical detector training with a research idea about unified representations. YOLOR includes model configurations, training code, evaluation scripts,... -
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Apex Up
Deploy infinitely scalable serverless apps, APIs and sites
Up deploys infinitely scalable serverless apps, APIs, and static websites in seconds, so you can get back to working on what makes your product unique. Up focuses on deploying “vanilla” HTTP servers so there’s nothing new to learn, just develop with your favorite existing frameworks such as Express, Koa, Django, Golang net/HTTP or others. Up currently supports Node.js, Golang, Python, Java, Crystal, and static sites out of the box. Up is platform-agnostic, supporting AWS Lambda and API Gateway as the first targets, you can think of Up as a self-hosted Heroku-style user experience for a fraction of the price, with security, flexibility, and scalability of AWS, just $ up and you’re done! ... -
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Differentiable Neural Computer
A TensorFlow implementation of the Differentiable Neural Computer
The Differentiable Neural Computer (DNC), developed by Google DeepMind, is a neural network architecture augmented with dynamic external memory, enabling it to learn algorithms and solve complex reasoning tasks. Published in Nature in 2016 under the paper “Hybrid computing using a neural network with dynamic external memory,” the DNC combines the pattern recognition power of neural networks with a memory module that can be written to and read from in a differentiable way. This allows the... -
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RegexAssistant
Regex Windows GUI app to help learn, create,& test Regular Expressions
RegexAssistant is a Regex GUI application to help learn, create, and test Regular Expressions. It's an open source stand alone Windows application. RegexAssistant is great for beginners and intermediate-advanced regex users. -It helps beginners to learn regex by providing examples and token cheat-sheet. -Intermediate-advanced users can use RegexAssistant to test complex expressions. -
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Microsoft Bot Framework SDK
Tool for building conversation applications
...With the Bot Framework SDK, developers can build bots that converse free-form or with guided interactions including using simple text or rich cards that contain text, images, and action buttons. Developers can model and build sophisticated conversation using their favorite programming languages including C#, JS, Python and Java or using Bot Framework Composer, an open-source, visual authoring canvas for developers and multi-disciplinary teams to design and build conversational experiences with Language Understanding, QnA Maker and sophisticated composition of bot replies (Language Generation). Checkout the Bot Framework ecosystem section to learn more about other tooling and services related to the Bot Framework SDK. ... -
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Gluon CV Toolkit
Gluon CV Toolkit
GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection,... -
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PyTorch SimCLR
PyTorch implementation of SimCLR: A Simple Framework
For quite some time now, we know about the benefits of transfer learning in Computer Vision (CV) applications. Nowadays, pre-trained Deep Convolution Neural Networks (DCNNs) are the first go-to pre-solutions to learn a new task. These large models are trained on huge supervised corpora, like the ImageNet. And most important, their features are known to adapt well to new problems. This is particularly interesting when annotated training data is scarce. In situations like this, we take the... -
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Kalman and Bayesian Filters in Python
Kalman Filter book using Jupyter Notebook
...This book is interactive. While you can read it online as static content, it's better to use it as intended. It is written using Jupyter Notebook, which allows you to combine text, math, Python, and Python output in one place. -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference... -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in... -
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TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the... -
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gditools
A Python program/library aimed at GD-ROM image files.
This Python program/library is designed to handle GD-ROM image (GDI) files. It can be used to list files, extract data, generate sorttxt file, extract bootstrap (IP.BIN) file and more. This project can be used in standalone mode, in interactive mode or as a library in another Python program (check the 'addons' folder to learn how). For your convenience, you can use the gditools.py GUI program supplied in the Files section (optional). -
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Emojicode
World’s only programming language that’s bursting with emojis
Emojicode is an open-source, full-blown programming language consisting of emojis. As a multi-paradigm language, Emojicode features object orientation, optionals, generics, closures, and protocols. Emojicode compiles native machine code using lots of optimizations that make your code fast. Emojicode comes with a comprehensive set of default packages. And you can easily write your own. We believe that Emojis have expressive force. Let’s use that to make programming more fun and accessible.... -
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wtfpython
Exploring and understanding Python through surprising snippets
...While some of the examples you see below may not be WTFs in the truest sense, but they'll reveal some of the interesting parts of Python that you might be unaware of. I find it a nice way to learn the internals of a programming language, and I believe that you'll find it interesting too! If you're an experienced Python programmer, you can take it as a challenge to get most of them right in the first attempt. You may have already experienced some of them before, and I might be able to revive sweet old memories of yours! -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action.