This workflow orchestrates multiple specialized agents to build a production-ready ML pipeline following modern MLOps best practices. The approach emphasizes:. Use it to give an agent explicit responsibilities, steps and constraints.

Few-shot learning enables LLMs to perform tasks by providing a small number of examples (typically 1-10) within the prompt. This technique is highly effective for tasks requiring specific formats, styles, or domain knowledge. Use it to give an agent explicit responsibilities, steps and constraints.

This roadmap is designed for aspirants with zero experience , focusing on free learning paths , projects , interview prep , and tools that are widely accepted in the industry. Use it as a repeatable review, validation or hardening pass.

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources. Use it to navigate the topic and choose relevant methods, papers or tools.

This repository contains a curated list of papers, PhD theses, datasets, and tools that are devoted to research on Machine Learning for Software Engineering. The papers are organized into popular research areas so that researchers can find recent papers and state-of-the-art appro. Use it to build a structured path from fundamentals to hands-on practice.

This is a collection of pointers to datasets/tasks/benchmarks pertaining to the intersection of machine learning and law. Use it to navigate the topic and choose relevant methods, papers or tools.

eBPF is a technology that can run sandboxed programs in the Linux kernel without changing kernel source code or loading kernel modules. By making the Linux kernel programmable, infrastructure software can leverage existing layers, making them more intelligent and feature-rich wit. Use it as a repeatable review, validation or hardening pass.

The official repository which contains the code and pre-trained models for our paper TAPEX: Table Pre-training via Learning a Neural SQL Executor. Use it to navigate the topic and choose relevant methods, papers or tools.

TRL is a cutting-edge library designed for post-training foundation models using advanced techniques like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), and Direct Preference Optimization (DPO). Built on top of the 🤗 Transformers ecosystem, TRL supports. Use it to navigate the topic and choose relevant methods, papers or tools.

This is a list of links to different freely available learning resources about computer programming, math, and science. Use it to build a structured path from fundamentals to hands-on practice.

This is a curated list of medical data for machine learning. This list is provided for informational purposes only, please make sure you respect any and all usage restrictions for any of the data listed here. Use it to ground design choices in named patterns, trade-offs and examples.

An interactive deep learning book with code, math, and discussions, based on the NumPy interface by Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola. With 900 pages, this seems to be one of the most comprehensive one-stop resources that goes from Linear Neural Networ. Use it to build a structured path from fundamentals to hands-on practice.

MLOps Zoomcamp: A Free 9-Week Course on Productionizing ML Services. Use it to build a structured path from fundamentals to hands-on practice.

LLM Zoomcamp: Free Course on Building LLM Applications with RAG, Agents & Vector Search Go from LLM basics to a production-ready AI assistant in 10 weeks. Use it to build a structured path from fundamentals to hands-on practice.

Data Engineering Zoomcamp: A Free 9-Week Course on Data Engineering Fundamentals. Use it to build a structured path from fundamentals to hands-on practice.

Found an awesome resource, article, book, tool, video, technical writer, speaker deck, etc.?. Use it as a repeatable review, validation or hardening pass.

code examples with explanations, different use cases and links to further readings. It is a playground because you may change or add the code to see how it works and test it out using assertions.

Email me, shoot me a DM, or make a pull request! ^^ This list is aimed at learning the craft of game development.