best-of-ml-python — 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
Pythonで使えるマシンラーニングライブラリを紹介している。
Python MLライブラリ
MLINFO COLLECTION
深層学習
記事一覧
2 / 45txtai — 💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
LLMを利用するために、セマンティック検索やLLMのオーケストレーションなどを行えるフレームワーク。
セマンティック検索
SolarWM — Open data and scalable training for long-horizon video world models.
Open data and scalable training for long-horizon video world models.
deep-learning
presidio — An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.
presidioは、テキスト、画像、構造化データを含む敏感データを検出、削除、マスク、アノニマイズするオープンソースフレームワークです。自然言語処理、パターンマッチング、カスタマイズ可能なパイプラインをサポートします。
データのプライバシーを保護する
ai-engineering-from-scratch — Learn AI Engineering! Learn it. Build it. Ship it for others.
このリポジトリでは、AIエンジニアリングのためのオープンソースプラットフォームであるMLflowを提供しています。
AIエンジニアリングのためのプラットフォーム
Propose-Filter-Release: Scaling Noise to Typical Sensitivity via Private Filtering
An estimator can be accurate and stable on typical data, yet sensitive to a few possible records. Differentially private mechanisms commonly scale their noise to the worst-case influence of a single…
deep-learning
Micro-Edits: Computational Support for Fine-Scale Edits in Film
In film editing, every frame matters. While macro, content-level edits shape the high-level narrative of a film, small local edits often control timing and direct visual attention.
deep-learning
Read, Allocate, Route: Role-Coupled Tokenization for Pixel-Space Generative Transformers
Pixel-space generative Transformers typically use one token per image patch, so capturing finer detail requires more tokens and makes global attention increasingly expensive. We observe that finer…
deep-learning
SwapBot: Tool-Centric Robot Manipulation via Interchangeable End-Effectors and Tactile Sensing
Robot manipulation in everyday environments inherently involves substantial tool usage. Seemingly simple household tasks, such as cooking pan-fried tofu, require forceful cutting, delicate brushing,…
deep-learning
SymAnt: Grounding Long-Horizon Action Anticipation with Adaptable Symbolic Priors
As robots and intelligent systems increasingly interact with humans, they must anticipate long sequences of future actions from only brief observations. While purely neural models typically require…
deep-learning
Finding Competitive Equilibria in Online Marketplaces with Platform Fees, Taxes, and Subsidies
We study equilibrium computation in multi-unit trading networks with valuations satisfying generalized full substitutes and agent- and transaction-specific piecewise-linear transfer functions. These…
deep-learning
An ODE-based Sampler for Discrete Diffusion Models
The marginals of a continuous diffusion model can be reproduced by a deterministic ordinary differential equation (ODE), known as the probability flow ODE, which provides a foundation for accelerated…
deep-learning
L3G-World: Real-Time Infinite World Generation with Latent 3D Gaussian Memory
Interactive world models generate visual content conditioned on user actions, yet maintaining spatial consistency over long-horizon exploration in real time remains challenging. Existing approaches…
deep-learning
When to Assist and What to Suggest: Joint Gating and Memory-Grounded Hint Generation in One Compact Decoder
Proactive assistants offer short, memory-grounded hints during a conversation, deciding when to assist and what to suggest. Current systems split this between a gate and a larger generator; we…
deep-learning
HairDeck: Animation-Ready Stylized Hair Cards from a Single Image
The hair of stylized characters in games and avatars is built from hair cards: artist-placed ribbons whose geometry is the visible hair, animated by spring bones. Existing image-based methods produce…
deep-learning
Beyond Ground Truth: A Heuristic Unsupervised Quality Assurance Engine for Diagnosing Calibrational Blindness in Dental Segmentation
In real-world clinical settings, dental X-ray segmentation using deep learning methods suffers from reliability issues. Even when the segmentation quality is bad, deep learning models show high…
deep-learning
RADIOlogy: A Single-Pass Approach to Training-Free Zero-Shot Anomaly Detection
Current zero-shot anomaly detection methods often rely on complex prompt-learning techniques or computationally expensive sliding-window strategies to achieve fine-grained visual alignment to detect…
deep-learning
Every Token Needs Its Own Teacher: Multi-teacher Adaptive On-policy Self-distillation
On-policy Self-distillation (OPSD) has proven effective for post-training large language models by constructing a teacher conditioned on privileged references. However, existing approaches keep the…
deep-learning
Comparing Human Role-Players and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns
This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially, we recorded role-playing…
deep-learning
FARMS: A Verifiable Foundation for Automated Computational Science
Automated computational science could accelerate discovery by selecting, adapting and developing numerical methods. This prospect requires mathematical knowledge that AI systems can interpret and…
deep-learning
Retrieval as Traversal: Value-Indexed Memory for Stateful Long-Context Agents
Long-context models repeatedly solve closely related retrieval problems. Attention or global retrieval can retain large stores, but each forward pass again searches for what matters.
deep-learning
Machine Learning-Based Detection of Mobile Money Scan Messages in Ghana: A Comparative Evaluation of Naive Bayes, Support Vector Machine, and Randon Forest Classifiers
Mobile money (MoMo) is Ghana's preferred retail payment channel, recording GHC518.4 billion in transactions in December 2025 and over 26.7 million active accounts (Graphic Online, 2026). This growth…
deep-learning
On the Fundamental Limits of Prefill-Based Decoding Length Prediction
Predicting how many tokens a large language model (LLM) will decode, using only prefill-phase hidden states, is a key primitive for inference scheduling. We show that current benchmarks conflate…
deep-learning
DAWN: Diffusion-based Alignment and unfastening Workflow Network
We present DAWN (Diffusion-based Alignment and unfastening Workflow Network), a hierarchical robotic framework designed to perform real-world, unfastening tasks through multi-modal sensory…
deep-learning