Search Results for "python (scikit-learn)" - Page 5
Sort By:
Showing 308 open source projects for "python (scikit-learn)"
View related business solutions-
Get Avast Free Antivirus with 24/7 AI-powered online scam detectionAward-winning antivirus protection, as well as protection against online scams, dangerous Wi-Fi connections, hacked accounts, and ransomware. It includes Avast Assistant, your built-in AI partner, which gives you help with suspicious online messages, offers, and more.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
TensorFlow Documentation
TensorFlow documentation
An end-to-end platform for machine learning. TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples. -
2
Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing what... -
3
sense2vec
Contextually-keyed word vectors
sense2vec (Trask et. al, 2015) is a nice twist on word2vec that lets you learn more interesting and detailed word vectors. This library is a simple Python implementation for loading, querying and training sense2vec models. For more details, check out our blog post. To explore the semantic similarities across all Reddit comments of 2015 and 2019, see the interactive demo. -
4
T81 558
Applications of Deep Neural Networks
Deep learning is a group of exciting new technologies for neural networks. Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network... -
Gen AI apps are built with MongoDB AtlasMongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
-
5
ScikitLearn.jl
Julia implementation of the scikit-learn API
The scikit-learn Python library has proven very popular with machine learning researchers and data scientists in the last five years. It provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia. Its primary goal is to integrate both Julia- and Python-defined models together into the scikit-learn framework. -
6
auto-sklearn
Automated machine learning with scikit-learn
auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. auto-sklearn frees a machine learning user from algorithm selection and hyperparameter tuning. It leverages recent advantages in Bayesian optimization, meta-learning and ensemble construction. Auto-sklearn 2.0 includes latest research on automatically configuring the AutoML system itself and contains a multitude of improvements which speed up the fitting the AutoML system. auto-sklearn... -
7
PyRx - Virtual Screening Tool
Virtual Screening software for Computational Drug Discovery
... it a valuable tool for Computer-Aided Drug Design. PyRx also includes chemical spreadsheet-like functionality and powerful visualization engine that are essential for Rational Drug Design. Please visits PyRx home page to learn more about PyRx and watch videos on how to use it. -
8
eduActiv8
A collection of interactive educational exercises
eduActiv8 is a free Open Source multi-platform educational application that aims to assist in learning various early education topics - from learning the alphabet and new words, colours, time to a wide range of maths-related subjects. eduActiv8 is a continuation of the development of the pySioGame project just under a new name. It is being developed on GitHub at: https://github.com/imiolek-ireneusz/eduActiv8 but 'compiled' releases are published here. The latest version has been... -
9
SOFA is a statistics, analysis, and reporting program with an emphasis on ease of use, learn as you go, and beautiful output.
-
Powering the best of the internet | FastlyEnsure your websites, applications and services can effortlessly handle the demands of your users with Fastly. Fastly’s portfolio is designed to be highly performant, personalized and secure while seamlessly scaling to support your growth.
-
10
NanoH5 (tsl2nano)
java bean / database driven zero code application framework
NanoH5 (or FullRelation) is a fullstack UI implementation framework providing a model driven design (MDA). Build a complete html5 application through a given class- or database-model without coding (coding APIs are available). -
11
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. Using industry-standard machine... -
12
<<Hack|Track GNU/Linux
Distro Penetrasing Live System Burn to USB Flash Disk & Run.
<<Hack|Track GNU/Linux is an open source operating system developed by the HTGL Project from Indonesia which provides penetration testing. -
13
... algorithms, it can analyze complex data, learn, and provide intuitive solutions. Developed in popular languages like Python, it is fully customizable and open for community contributions and improvements. TAT (Ton Auto Trade) Bot is an advanced automated trading bot built for Ton. It is designed to employ a range of sophisticated trading strategies to maximize profits and provide hands-off trading automation. This bot is perfect for those looking to take advantage of market opportunities in the
-
14
YoungerSibling
YoungerSibling: Cross-platform OSINT tool for quick data gathering.
YoungerSibling is a Python-based terminal utility script designed for educational purposes. It provides a set of useful tools to perform tasks like searching the web, performing lookups (Google search, IP lookup, username lookup, etc.), and extracting metadata from images, directly from the terminal. This project aims to help students, developers, and hobbyists learn about web scraping, API usage, and terminal interaction with Python. -
15
Flashcard App
This is an app that will help you learn and prosper in any subject!
A lightweight but effective Flashcard based learning app to study and memorize using a reward system, built using python and the customtkinter library. Here you can create flashcards and quiz yourself on any topic you like, save the flashcards for later use or simply import one with the correct format. Give yourself hints, earn points and have fun! Play quiz with your friends see who gets the most points. Here almost anything is customizable. And forgive me if there are any bugs... -
16
Entropy Linux
Arch based, Modern, Midweight, Practical, Experimental, AMD, Szmelc
Based on Arch. Built for Power Users and Sysadmins. Built for those who demand control over their system. Optimized for AMD™, it features a global dark theme and a suite of powerful tools for advanced users. Developed by two lead devs and their squad, it’s raw, unpolished, and built for those who love to tinker, learn, and push boundaries. Why Entropy? Power & Flexibility: Designed for power users, sysadmins, and DevOps pros. Advanced Toolset: Custom utilities to boost productivity... -
17
Advanced Division
Divide numbers with recurring decimals
Library / application for dividing numbers with recurring decimals. Written in JavaScript, Python and Dart. Learn more: https://advdiv.ratajs.cz/ Installation instructions: https://sourceforge.net/projects/advanced-division/files/ -
18
LabRPS
Random phenomena generator
... reseachers in related fields to quickly implement new simulation methods programmatically in their new research work based on the existing works, help engineers to numerically generate random phenomena in a more realistic way, helps students and new comers to this field to learn quickly. It is highly modular and is integrated with a data visualizer which can generate different types of publication quality 2D and 3D plots (such as line, scatter, bar, pie -
19
PyPingMon
A simple ping server monitor
PyPingMon is a server monitoring program written in Python. At the specified interval it uses a single ping command to check if a server is available. This is my first Python program. I chose this particular type of program because I wanted to write my own server monitor and this was a great way to learn how to code in Python. -
20
WhakerPy
Whakerpy - A light web application framework
Whakerpy is a simple library useful to create dynamic HTML content; it's a light web application framework. Create and manipulate HTML from the power of Python: - Easy to learn. Consistent, simple syntax. - Flexible and easy usage. - Create HTML pages dynamically - Can save as static files, and/or - Run locally with its httpd server and response "bakery" system. Access the documentation: <https://whakerpy.sourceforge.io>. -
21
OpenAI Swarm
Framework exploring ergonomic, lightweight multi-agent orchestration
Swarm is an experimental educational framework developed by OpenAI that focuses on lightweight, ergonomic multi-agent orchestration. It is designed for developers interested in learning about the coordination and execution of multiple agents in a controlled, scalable environment. The framework emphasizes simplicity and testability, allowing users to explore agent-to-agent communication through basic constructs like Agent and handoffs. Swarm is well-suited for applications that require... -
22
Shennina
Automating Host Exploitation with AI
... to identify recommended exploits for the attacks, and then attempts to test and attack the targets. If the attack succeeds, Shennina proceeds with the post-exploitation phase. The AI engine is initially trained against live targets to learn reliable exploits against remote services. Shennina also supports a "Heuristics" mode for identfying recommended exploits. -
23
DeepCTR-Torch
Easy-to-use,Modular and Extendible package of deep-learning models
... features and some dense numerical features. Low-order Extractor learns feature interaction through product between vectors. Factorization-Machine and it’s variants are widely used to learn the low-order feature interaction. High-order Extractor learns feature combination through complex neural network functions like MLP, Cross Net, etc. -
24
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... -
25
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.
