📘 New Release from Deepsim Press
We are pleased to announce the publication of:
Practical Data Modeling and Machine Learning with Python
From Data Preparation to Model Evaluation and Optimization
This book presents a structured and practical approach to data modeling, emphasizing the complete workflow—from feature engineering and statistical modeling to machine learning, evaluation, and optimization.
Rather than focusing on isolated techniques, it highlights how to build models that are reliable, interpretable, and applicable in real-world scenarios.
Key topics include:
• Data preparation and feature engineering
• Regression and classification models
• Ensemble methods and model improvement
• Validation strategies and evaluation metrics
• Hyperparameter tuning and model optimization
• Model interpretation and explainability
This title is part of the Practical Data Science with Python series, designed to guide readers from foundational analysis to advanced modeling and real-world applications.
