Description
Machine Learning with Spark and Python provides comprehensive coverage of essential techniques for predictive analytics. This Indian adaptation, authored by Michael Bowles, bridges the gap between theoretical concepts and practical implementation using two of the most popular tools in data science.
The book guides readers through building scalable machine learning models using Apache Spark and Python programming. It covers fundamental algorithms, data preprocessing, feature engineering, and model evaluation techniques necessary for real-world applications. The content is tailored to help data scientists and engineers implement predictive analytics solutions efficiently.
With practical examples and hands-on exercises, this second edition equips professionals with the skills to handle large-scale datasets and deploy production-ready machine learning systems. Whether you’re beginning your ML journey or enhancing your existing skills, this adaptation provides relevant insights for the Indian tech landscape and global practices.
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