Scaling Machine Learning with Spark

Explore the intricacies of building scalable machine learning solutions with Apache Spark in this insightful GOTO Book Club interview featuring Adi Polak and Holden Karau. Delve into the world of distributed computing and machine learning as these experts discuss their book "Scaling Machine Learning with Spark." Learn about managing the ML lifecycle with MLflow, data preprocessing with Spark, feature engineering, model training with MLlib, and building pipelines. Discover how to combine Spark's power with deep learning, work with distributed TensorFlow, and scale machine learning using PyTorch. Gain valuable insights into when and why to use various technologies in the Apache Spark ecosystem, including Spark MLlib, MLflow, TensorFlow, and PyTorch. Perfect for data scientists and ML practitioners looking to enhance their understanding of end-to-end distributed ML workflows.