Apache Spark for Machine Learning
Build and deploy high-performance big data AI solutions for large-scale clusters
Created by Deepak Gowda
Explore how to process and analyze massive datasets for machine learning using Apache Spark. Gain practical skills to build, train, and deploy models that scale across large clusters. Tackle real-world data science challenges with proven techniques and hands-on coding examples.
Packt | Nov 2024 | 306 min
What You Will Learn
You will work through real-world coding examples and practical exercises that show how to use Spark for data processing, feature engineering, and model building. Step by step, you will learn to apply both supervised and unsupervised learning algorithms, optimize workflows, and deploy models at scale. The focus is on hands-on experience and solving realistic problems.
Key Features
- Analyze big data efficiently to extract actionable insights for machine learning
- Train and optimize models on large datasets using scalable Spark clusters
- Apply practical strategies for preprocessing, deployment, and model tuning
Target Audience
Designed for data scientists, machine learning engineers, and data engineers with some experience in Python or big data tools. If you want to deepen your skills in scalable machine learning, handle large datasets, or prepare for technical interviews focused on big data, you will find these techniques and workflows highly valuable.
