📮 Machine Learning for Tabular Data by Mark Ryan (.ePUB)

Machine Learning for Tabular Data covers classic Machine Learning techniques like gradient boosting, and more contemporary Deep Learning approaches. By the time you’re finished, you’ll be equipped with the skills to apply Machine Learning to the kinds of data you work with every day. Machine Learning can accelerate everyday business chores like account reconciliation, demand forecasting, and customer service automation—not to mention more exotic challenges like fraud detection, predictive maintenance, and personalized marketing. This book shows you how to unlock the vital information stored in spreadsheets, ledgers, databases and other tabular data sources using gradient boosting, Deep Learning, and Generative AI. Machine Learning for Tabular Data delivers practical ML techniques to upgrade every stage of the business data analysis pipeline. In it, you’ll explore examples like using XGBoost and Keras to predict short-term rental prices, deploying a local ML model with Python and Flask, and streamlining workflows using large language models (LLMs). Along the way, you’ll learn to make your models both more powerful and more explainable. For readers experienced with Python and the basics of Machine Learning.

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