Popular GitHub Repositories for Product Categorization

Opiniated RAG for integrating GenAI in your apps ? Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama. Any Vectorstore: PGVector, Faiss. Any Files. Anyway you want.

notes for software engineers getting up to speed on new AI developments. Serves as datastore for https://latent.space writing, and product brainstorming, but has cleaned up canonical references under the /Resources folder.

The best apps in the AI era aren’t solo experiences—they’re collaborative. Liveblocks provides customizable pre?built features to make your product multiplayer, engaging, and AI?ready. All without derailing your roadmap.

Open-source Visual programming for backend logic that integrates with existing codebases. Flyde bridges the gap between technical and non-technical team members. Product managers, designers, and backend developers can collaborate on the same visual flows.

Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.

The Machine Learning & Deep Learning Compendium was a list of references in my private & single document, which I curated in order to expand my knowledge, it is now an open knowledge-sharing project compiled using Gitbook.

Trench — Open-Source Analytics Infrastructure. A single production-ready Docker image built on ClickHouse, Kafka, and Node.js for tracking events, page views. Easily build product analytics dashboards, LLM RAGs, observability platforms, or any other analytics product.

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

bestblogs.dev - 汇集顶级编程、人工智能、产品、科技文章，大语言模型摘要评分辅助阅读，探索编程和技术未来

WebWhiz allows you to create an AI chatbot that knows everything about your product and can instantly respond to your customer's queries.

Collect various AI products | 搜集各种 AI 工具

Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.

Sample to envision intelligent apps with Microsoft's Copilot stack for AI-infused product experiences.

Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019

Training of Locally Optimized Product Quantization (LOPQ) models for approximate nearest neighbor search of high dimensional data in Python and Spark.

PYthon For Homomorphic Encryption Libraries, perform encrypted computations such as sum, mult, scalar product or matrix multiplication in Python, with NumPy compatibility. Uses SEAL/PALISADE as backends, implemented using Cython.

Connect your AI app directly to your data with a full stack solution. Fully connected Agentic Graph RAG pipelines mean you can focus on fine tuning your app and not building data infrastructure.

Code for reco-gym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising

User-Centered Product Development Prompt Templates

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