Search Results for "self learning" - Page 10
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Showing 337 open source projects for "self learning"
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SimSiam
PyTorch implementation of SimSiam
SimSiam is a PyTorch implementation of “Exploring Simple Siamese Representation Learning” by Xinlei Chen and Kaiming He. The project introduces a minimalist approach to self-supervised learning that avoids negative pairs, momentum encoders, or large memory banks—key complexities of prior contrastive methods. SimSiam learns image representations by maximizing similarity between two augmented views of the same image through a Siamese neural network with a stop-gradient operation, preventing feature collapse. ... -
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neurojs
A JavaScript deep learning and reinforcement learning library
...The framework supports neural network architectures and reinforcement learning methods such as deep Q-networks and actor-critic algorithms. Several interactive demonstrations included with the project illustrate how neural networks can be used to train agents in simulated tasks, including a browser-based self-driving car example. These demos allow users to visualize how reinforcement learning agents improve their behavior over time as they receive rewards and update their neural networks. -
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Open Application Model
Open Application Model (OAM)
Open Application Model (OAM) is a set of standard yet higher-level abstractions for modeling cloud-native applications on top of today's hybrid and multi-cloud environments. Focused on application rather than container or orchestrator, Open Application Model brings modular, extensible, and portable design for defining application deployment with higher level API. This is the key to enabling simple, consistent yet robust application delivery across hybrid environments including Kubernetes,... -
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Self-Attentive Parser
High-accuracy NLP parser with models for 11 languages
LightAutoML is an automated machine learning (AutoML) framework developed by Sberbank AI Lab, designed to facilitate the development of machine learning models with minimal human intervention. -
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Opyrator
Turns your machine learning code into microservices with web API
Instantly turn your Python functions into production-ready microservices. Deploy and access your services via HTTP API or interactive UI. Seamlessly export your services into portable, shareable, and executable files or Docker images. Opyrator builds on open standards - OpenAPI, JSON Schema, and Python type hints - and is powered by FastAPI, Streamlit, and Pydantic. It cuts out all the pain for productizing and sharing your Python code - or anything you can wrap into a single Python... -
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BitTiger
Lifelong Learning University from Silicon Valley
BitTiger is an extensive open educational repository that functions as a self-guided curriculum covering a wide range of topics in computer science, artificial intelligence, blockchain, system design, and technical interview preparation. Rather than being a traditional software application, it is structured as a knowledge base composed of curated learning materials, tutorials, and practical case studies designed to simulate real-world problem solving. -
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Data Science Notes
Curated collection of data science learning materials
Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. ... -
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code-nav
Professional programming navigation
Programming Navigation is not just a website, but a complete ecology with the goal of "helping everyone discover high-quality programming resources and improve learning efficiency". It contains multiple sub-projects, and the technology stack includes React, Java SpringBoot, Tencent Cloud Development, etc., all of which are open source for everyone to learn, so that you can easily develop beautiful information navigation websites! Most of the programming navigation websites are in disrepair and have good navigation, but they are limited in search and classification, and they do not have functions such as self-recommendation and liking, so they are not sustainable. -
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Mega Project List
List of practical projects that anyone can solve in any prog language
Mega Project List by Karan Goel is a massive list of practical programming project ideas that anyone can solve in any programming language, organized into logical categories (Numbers, Classic Algorithms, Data Structures, Text, Networking, Web, Files, Graphics & Multimedia, Security, etc.). The concept is simple but powerful: instead of just memorizing algorithms, you pick a project (for example “Binary to Decimal and Back Converter”), implement it in your favorite language, and gradually... -
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NoisePage
Self-Driving Database Management System
NoisePage is a relational database management system (DBMS) designed from the ground up for autonomous deployment. It uses integrated machine learning components to control its configuration, optimization, and tuning. The system will support automated physical database design (e.g., indexes, materialized views, sharding), knob configuration tuning, SQL tuning, and hardware capacity/scaling. Our research focuses on building the system components that support such self-driving operations with little to no human guidance. ... -
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English2Cards
English Learning software
English2Cards is a smart English learning program designed to improve your listening & speaking skills without Internet connection using great learning files. The program repeatedly reviews the educational cards at different times so that you can remember the new words and phrases that you have learned and be able to use them in real conversations easily and without thinking. During learning you can remember the words in the text and also get the translation, pronunciation and examples of... -
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Multi-Agent Emergence Environments
Environment generation code for the paper "Emergent Tool Use"
multi-agent-emergence-environments is an open source research environment framework developed by OpenAI for the study of emergent behaviors in multi-agent systems. It was designed for the experiments described in the paper and blog post “Emergent Tool Use from Multi-Agent Autocurricula”, which investigated how complex cooperative and competitive behaviors can evolve through self-play. The repository provides environment generation code that builds on the mujoco-worldgen package, enabling... -
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VideoPlayerDemo
Encapsulate ijkplay player, self-implementing bottom-streaming
VideoPlayerDemo is a multimedia demonstration project that showcases video playback capabilities within a mobile or desktop application environment. It focuses on integrating FFmpeg-based decoding with a custom rendering pipeline to display video content efficiently. The project demonstrates how to handle media streams, synchronize audio and video, and manage playback controls. It serves as a learning resource for developers exploring media frameworks and playback architectures. The... -
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8cc C Compiler
Compiler for the C programming language
8cc C Compiler is a small and educational C compiler designed to support the C11 standard while maintaining a compact and easy-to-understand codebase. It was created as a hobby project with the goal of demonstrating how a compiler works internally, making it a valuable resource for learning compiler design. The project includes core components such as a lexer, parser, and preprocessor, allowing users to explore each stage of the compilation process. One of its notable features is its ability... -
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DeepCluster
Deep Clustering for Unsupervised Learning of Visual Features
DeepCluster is a classic self-supervised clustering-based representation learning algorithm that iteratively groups image features and uses the cluster assignments as pseudo-labels to train the network. In each round, features produced by the network are clustered (e.g. k-means), and the cluster IDs become supervision targets in the next epoch, encouraging the model to refine its representation to better separate semantic groups. -
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Mathematics
Accumulation of mathematical knowledge, matrix numerical optimization
Mathematics is a comprehensive collection of notes, resources, and references spanning a wide range of mathematical topics. The repository organizes material across pure and applied mathematics, including calculus, linear algebra, probability, statistics, and optimization. It also extends into computational and algorithmic applications of mathematics, making it a useful reference for both academic study and practical problem-solving. The goal is to provide learners, researchers, and... -
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pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
...Each section includes runnable code examples that progressively increase in complexity, helping learners build intuition while practicing hands-on implementation. Because the tutorials are concise and practical, the project is widely used in classrooms and self-study environments. Overall, it functions as both a learning curriculum and a quick reference for common PyTorch workflows. -
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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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Computer Vision Pretrained Models
A collection of computer vision pre-trained models
...Instead of building a model from scratch to solve a similar problem, we can use the model trained on other problem as a starting point. A pre-trained model may not be 100% accurate in your application. For example, if you want to build a self-learning car. You can spend years building a decent image recognition algorithm from scratch or you can take the inception model (a pre-trained model) from Google which was built on ImageNet data to identify images in those pictures. The model generates bounding boxes and segmentation masks for each instance of an object in the image. ... -
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30 Days of Swift
A self-taught project to learn Swift
30DaysofSwift is a challenge-style collection of Swift exercises and learning tasks meant to be tackled over 30 days (or more flexibly). Each “day” introduces a coding problem, concept, or mini project that builds on previous days: for example, fundamentals on day 1, optionals and control flow, Swift data structures, closures, protocol programming, UI interaction, etc., culminating in more advanced topics or sample apps. Solutions, hints, or sample projects accompany many of the prompts,... -
21
End-to-End Negotiator
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
End-to-End Negotiator is a PyTorch-based research framework developed by Facebook AI Research to train neural agents capable of conducting strategic negotiations in natural language. The project implements the models presented in two key papers: “Deal or No Deal? End-to-End Learning for Negotiation Dialogues” and “Hierarchical Text Generation and Planning for Strategic Dialogue”. It enables agents to plan, reason, and communicate effectively to maximize outcomes in multi-turn negotiations over shared resources. The framework provides code for both supervised learning (training from human dialogue data) and reinforcement learning (via self-play and rollout-based planning). ... -
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intelligent thinking system solving
An approach where computer solves problems like a human brain does;
The intelligent, thinking systems solving project uses a method whereby the computer solves the problem in a way a biological way does. The result of this is that it can learn and emulate a behavior or strategy. Two examples of the process use the game of chess and the game of go. -
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Python Machine Learning
The "Python Machine Learning (2nd edition)" book code repository
This repository accompanies the well-known textbook “Python Machine Learning, 2nd Edition” by Sebastian Raschka and Vahid Mirjalili, serving as a complete codebase of examples, notebooks, scripts and supporting materials for the book. It covers a wide range of topics including supervised learning, unsupervised learning, dimensionality reduction, model evaluation, deep learning with TensorFlow, and embedding models into web apps. -
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PyHubs
Hubness-aware machine learning in Python
PyHubs is a machine learning library developed in Python containing implementations of hubness-aware machine learning algorithms together with some useful tools for machine learning experiments. According to our recent observation, old versions of PyHubs (such as 1.2.1) does not provide correct results with new versions of numpy (such as 1.16), however, we think that the most recent version of PyHubs (1.3) works correctly with new versions of numpy as well. -
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swirl
Learn R, in R
swirl is an R package that allows interactive, in-R learning of statistics, data science, R programming etc. The idea is that you load swirl in R, and it presents you with lessons (within R’s console or RStudio) that ask you to type commands, check results, and progress through tutorial material—without leaving the R environment. It is used for teaching R, especially for beginners, as well as for self-paced learning of packages, data manipulation, visualization, etc. ...
