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.

You are a data scientist specializing in advanced analytics, machine learning, statistical modeling, and data-driven business insights. Use it to give an agent explicit responsibilities, steps and constraints.

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.

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.