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Collection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.

A collection of analysis, and machine learning techniques for time series forecasting w/ Prometheus metrics

Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.

Some practice and collection of machine learning

This repository contains a collection of books I have downloaded related to **Mathematics**, **Artificial Intelligence (AI) & Machine Learning (ML)**, and **Algorithms**. Some of these books I have read, while others are on my reading list.

A collection of examples for the ML.NET machine learning package from Microsoft

W3C Strategic Highlights September 2019 This report was prepared for the September 2019 W3C Advisory Committee Meeting (W3C Member link). See the accompanying W3C Fact Sheet — September 2019. For the previous edition, see the April 2019 W3C Strategic Highlights. For future editions of this repo... Read more

A collection of Machine Learning examples to get started with deploying RAPIDS in the Cloud

A handpicked collection of resources for Python developers in data engineering, machine learning, and AI. Inside, you'll discover a neatly arranged selection of frameworks, libraries, and tools crucial for machine learning, ETL, ORM, data/schema validation, database migration, and more, all focus... Read more

This project presents a Blockchain-Enabled Federated Learning (BFL) framework designed to address critical challenges in privacy-preserving AI. Traditional machine learning requires centralized data collection, creating privacy risks and regulatory concerns, while standard federated learning