📚 AI ML Books Repository

Welcome to the AI ML Books repository! 🚀 This collection features a curated set of resources focusing on Artificial Intelligence (AI), Machine Learning (ML), Big Data Engineering, Data Analytics, and Cloud-based tools. These books cover essential tools and frameworks such as Apache Spark, Hadoop, Python, and Azure Databricks to help you dive deeper into the field of AI/ML and Big Data.

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📖 What's Inside?

Here’s a quick overview of the content:

1. Big Data and Apache Spark

• Sams Teach Yourself Apache Spark in 24 Hours – Jeffrey Aven
• Next-Generation Big Data – Butch Quinto
• Data Engineering with Apache Spark and Delta Lake – annas-archive
• Stream Processing with Apache Spark – Gerard Maas, Francois Garillot
• Beginning Apache Spark 3 – Hien Luu
• Learning Spark: Lightning-Fast Big Data Analysis – Holden Karau et al.
• Apache Spark Graph Processing – Rindra Ramamonjison

2. Hadoop and Data Streaming

• Hadoop in 24 Hours – Jeffrey Aven
• Building Data Streaming Applications with Apache Kafka – Manish Kumar, Chanchal Singh
• Hadoop: The Definitive Guide – Tom White

3. Cloud and Data Engineering

• Mastering Machine Learning on AWS – Dr. Saket S.R. Mengle, Maximo Gurmendez
• Azure Data Engineering Cookbook – Nagaraj Venkatesan, Ahmad Osama
• Azure Databricks Cookbook – Phani Raj, Vinod Jaiswal
• Beginning Apache Spark Using Azure Databricks – Robert Ilijason
• Modern Data Engineering with Apache Spark – S. Haines

4. Python Programming and Data Analytics

• Learning Python
• Python Programming for Beginners
• Python for Data Analysis

5. Advanced Data Applications and Frameworks

• Designing Data-Intensive Applications – Martin Kleppmann
• Scala Programming for Big Data Analytics – Irfan Elahi
• PySpark Cookbook – Tomasz Drabas, Denny Lee

6. In-Memory Analytics

• In-Memory Analytics with Apache Arrow

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🚀 Usage

1. Clone the Repository

Use the following command to clone this repository to your local machine:

git clone https://github.com/your-username/AI-ML-Books.git