Search Results for "python mini project" - Page 2
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Showing 750 open source projects for "python mini project"
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NBA Sports Betting Machine Learning
NBA sports betting using machine learning
NBA-Machine-Learning-Sports-Betting is an open-source Python project that applies machine learning techniques to predict outcomes of National Basketball Association games for analytical and betting-related research. The system gathers historical team statistics and game data spanning multiple seasons, beginning with the 2007–2008 NBA season and continuing through the present. Using this dataset, the project constructs matchup features that represent team performance trends and contextual information about each game. ... -
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Pocket TTS
A TTS that fits in your CPU (and pocket)
Pocket TTS is a lightweight text-to-speech project designed to run efficiently on CPUs, targeting developers who want local speech generation without depending on GPUs or hosted web APIs. It is built to feel practical in everyday applications, where installation and usage should be as simple as adding a dependency and calling a function. The project focuses on keeping the runtime footprint manageable while still producing natural-sounding speech, which makes it attractive for offline tools,... -
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reverse-SynthID
Reverse engineering Gemini's SynthID detection
Reverse-SynthID is a research-focused project that analyzes and reverse-engineers Google’s SynthID watermarking system used in AI-generated images. It leverages signal processing and spectral analysis techniques to identify hidden watermark patterns without access to proprietary encoding methods. The project introduces a multi-resolution “SpectralCodebook” that maps watermark characteristics across different image sizes. Using this approach, it can detect SynthID watermarks with high... -
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fireworks-tech-graph
Claude Code skill for generating production-quality SVG+PNG technical
fireworks-tech-graph is an AI-driven project focused on building structured knowledge graphs that map relationships between technologies, concepts, and entities within technical domains. It aims to transform unstructured information into interconnected graphs that can be queried and analyzed for insights, making it easier to understand complex ecosystems such as software stacks or research fields. The system likely leverages AI techniques for entity extraction, relationship mapping, and... -
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Mlxtend
A library of extension and helper modules for Python's data analysis
Mlxtend (machine learning extensions) is a Python library of useful tools for day-to-day data science tasks. -
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GraphRAG
A modular graph-based Retrieval-Augmented Generation (RAG) system
The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs. -
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Applio
A simple, high-quality voice conversion tool focused on ease of use
Applio is a high-quality voice conversion toolkit designed to make modern RVC/VITS-based voice cloning accessible to non-experts. It focuses strongly on ease of use: installation scripts for Windows, Linux, and macOS set up dependencies and then launch a browser-based Gradio interface. Within that interface, users can train and run voice conversion models for tasks like singing conversion, speech-to-speech transformation, and voice cloning. The project is structured to be flexible through... -
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Video-subtitle-remover (VSR)
AI tool that removes hardcoded subtitles and text from videos locally
Video Subtitle Remover is an AI-based application designed to remove hardcoded subtitles from videos and generate new files without the embedded text. Video Subtitle Remover analyzes video frames and detects subtitle regions, then replaces the removed areas using an AI algorithm that fills the space with reconstructed visual content. This process aims to maintain the original resolution and visual continuity of the video after subtitle removal. It allows users to define a specific subtitle... -
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GPU Puzzles
Solve puzzles. Learn CUDA
GPU Puzzles is an educational project designed to teach GPU programming concepts through interactive coding exercises and puzzles. Instead of presenting traditional lecture-style explanations, the project immerses learners directly in hands-on programming tasks that demonstrate how GPU computation works. The exercises are implemented using Python with the Numba CUDA interface, which allows Python code to compile into GPU kernels that run on CUDA-enabled hardware. ... -
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Ling-V2
Ling-V2 is a MoE LLM provided and open-sourced by InclusionAI
Ling-V2 is an open-source family of Mixture-of-Experts (MoE) large language models developed by the InclusionAI research organization with the goal of combining state-of-the-art performance, efficiency, and openness for next-generation AI applications. It introduces highly sparse architectures where only a fraction of the model’s parameters are activated per input token, enabling models like Ling-mini-2.0 to achieve reasoning and instruction-following capabilities on par with much larger... -
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nanochat
The best ChatGPT that $100 can buy
nanochat is a from-scratch, end-to-end “mini ChatGPT” that shows the entire path from raw text to a chatty web app in one small, dependency-lean codebase. The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. Its north star is approachability and... -
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EconML
Python Package for ML-Based Heterogeneous Treatment Effects Estimation
EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal of combining state-of-the-art machine learning techniques with econometrics to bring automation to complex causal inference problems. -
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nanocode
Minimal Claude Code alternative. Single Python file, zero dependencies
...The project exemplifies how lightweight architectures can still support practical agent workflows without complex infrastructure, making it suitable for developers exploring agent frameworks or building custom coding assistants. -
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EPUB to Audiobook Converter
EPUB to audiobook converter, optimized for Audiobookshelf
...The tool offers advanced options such as controlling chapter ranges, handling paragraph detection via newline modes, removing endnote markers, and using regex-based search-and-replace files to tweak pronunciations. It can be run directly with Python or via Docker. -
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Toloka-Kit
Toloka-Kit is a Python library for working with Toloka API
...AutoQuality feature which automatically finds the best fitting quality control rules for your project. -
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notebooklm-py
Unofficial Python API and agentic skill for Google NotebookLM
...The project covers notebook management, source ingestion, conversational querying, research workflows, and sharing controls, while also enabling the generation of a wide range of study and media artifacts. These outputs include audio overviews, videos, slide decks, infographics, quizzes, flashcards, reports, data tables, and mind maps, with configurable formats and export options. -
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Docling
Get your documents ready for gen AI
Docling is an open-source document processing toolkit built to prepare diverse content types for modern generative AI and data workflows. The project focuses on converting and parsing many document formats into a unified structured representation that downstream systems can easily consume. It supports advanced PDF understanding, including layout detection, table extraction, and reading order analysis, enabling high-fidelity document intelligence pipelines. Docling is designed to run efficiently on commodity hardware and can be used both as a Python API and a command-line tool. ... -
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Agently 4
Build GenAI application quick and easy
...It abstracts away boilerplate around model API calls, tool usage, prompt management, and workflow state. The project aims at production-grade GenAI application development rather than just one-off scripts — you’ll find examples of news gathering, agentic workflows, control systems, etc. It is licensed under Apache-2.0, allowing commercial use and modification. Because it's built in Python, it integrates easily with existing data pipelines, databases, and agent architectures. -
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MLX-Audio
A text-to-speech, speech-to-text and speech-to-speech library
...Because it uses MLX and targets Apple Silicon, inference is fast and can take advantage of hardware acceleration and quantization for efficient on-device performance. The project provides a straightforward CLI (mlx_audio.tts.generate) as well as a Python API for programmatic generation of audio, including parameters for voice choice, speed, language hints, output format, and sample rate. It includes examples such as audiobook generation to demonstrate long-form synthesis and joined audio segments. On top of that, MLX-Audio offers a modern web interface powered by FastAPI, with real-time waveform and 3D visualizations, file upload, and audio management. -
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Sunfish
Sunfish: a Python Chess Engine in 111 lines of code
...The project is often used as an educational tool for understanding game AI, search algorithms, and evaluation functions without the complexity of larger engines. It includes a simple UCI-compatible interface, allowing it to be integrated with graphical chess interfaces or used in terminal-based gameplay. The codebase is intentionally minimal, making it ideal for experimentation, modification, and learning purposes. -
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OpenPlanter
Language-model investigation agent with a terminal UI
OpenPlanter is an open-source Python project focused on building an intelligent automated planting or gardening system powered by software control and data processing. The repository is designed to help developers and hobbyists create programmable plant management workflows that can monitor, schedule, and optimize growing conditions. It emphasizes automation and extensibility, allowing integration with sensors, environmental data, and control logic for smart cultivation setups. ... -
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BrowserGym
A Gym environment for web task automation
BrowserGym is an open framework for web task automation research that exposes browser interaction as a Gym-style environment for training and evaluating agents. It is intended for researchers building web agents rather than for end users looking for a consumer automation product. The project provides a common environment where agents can interact with websites, execute tasks, and be evaluated against standardized benchmarks. One of its main strengths is that it bundles several important... -
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Spec Kit
Toolkit to help you get started with Spec-Driven Development
Spec Kit is an open-source toolkit designed to enable specification-driven development workflows powered by AI coding assistants. It introduces a structured process in which developers define detailed specifications first, then allow AI tools to generate plans, tasks, and implementation code aligned with those requirements. The toolkit provides scaffolding, prompt templates, and automation scripts that help teams maintain a clear source of truth throughout the development lifecycle. By... -
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Mistral Vibe CLI
Minimal CLI coding agent by Mistral
Mistral Vibe is an AI-powered “vibe-coding” command-line interface (CLI) and coding-assistant framework built by Mistral AI to let developers write, refactor, search, and manage code through natural language and context-aware automation, rather than manual typing only. It aims to take developers out of repetitive boilerplate and let them stay “in the flow”: you can ask the tool to generate functions, refactor code, search across the codebase, manipulate files, commit changes via Git, or run... -
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skfolio
Python library for portfolio optimization built on top of scikit-learn
skfolio is a Python library designed for portfolio optimization and financial risk management that integrates closely with the scikit-learn ecosystem. The project provides a unified machine learning-style framework for building, validating, and comparing portfolio allocation strategies using financial data. By following the familiar scikit-learn API design, the library allows quantitative researchers and developers to apply techniques such as model selection, cross-validation, and hyperparameter tuning to portfolio construction workflows. ...
