Python scripts for feature engineering: master data preparation (10 Ergebnisse)

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.

Paperback. Zustand: new. Paperback. Stop wasting hours cleaning messy datasets before they derail your machine learning projectsPython Scripts for Feature Engineering: Master Data Preparation gives you a practical, code driven framework for transforming raw data into high quality features ready for analytics and machine learning. Instead of relying on theory heavy explanations, this book focuses on real world workflows, reusable Python scripts, and proven techniques used throughout the data preparation process.Learn to clean inconsistent datasets, engineer meaningful features, and automate preparation pipelines using Pandas, NumPy, and Scikit Learn. Every chapter is designed to help you move from raw data to model ready datasets with greater speed, accuracy, and confidence.Build cleaner datasets and reduce data preparation time through repeatable workflowsMaster feature creation, transformation, encoding, scaling, and dimensionality reduction techniquesDevelop production ready data preparation pipelines that improve scalability and maintainabilityWritten for data scientists, machine learning engineers, analysts, developers, and technical professionals who need reliable feature engineering solutions in real world environments. Based on practical implementation experience and industry standard workflows used in modern data science projects.You'll gain the exact techniques needed to prepare high quality data before poor feature design undermines your results This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Zustand: new. Paperback. Stop fragile feature engineering workflows before they create inconsistent models, unreliable predictions, and costly deployment failures. Fix feature engineering challenges in your machine learning projects without relying on disconnected scripts, manual preprocessing, or hard to maintain workflows. This book gives you a practical implementation guide for building production ready feature engineering systems that scale from development to deployment not toy examples or theory heavy discussions. Learn to design automated pipelines, manage feature transformations consistently, and deploy reliable preprocessing frameworks using industry standard Python tools and proven engineering practices. Build reusable feature engineering pipelines that reduce development time and improve model consistency. Master production-focused workflows, automation strategies, and deployment ready preprocessing systems. Create scalable feature management solutions that support real world machine learning applications. Written for data scientists, machine learning engineers, AI developers, analytics professionals, and technical practitioners who need reliable feature engineering workflows in production environments. Based on practical implementation patterns, deployment challenges, and real world machine learning system design. You'll get exact techniques to automate feature engineering workflows, maintain data consistency, and deploy scalable preprocessing systems before small issues become production emergencies. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Zustand: new. Paperback. Stop wasting hours cleaning messy datasets before they derail your machine learning projectsPython Scripts for Feature Engineering: Master Data Preparation gives you a practical, code driven framework for transforming raw data into high quality features ready for analytics and machine learning. Instead of relying on theory heavy explanations, this book focuses on real world workflows, reusable Python scripts, and proven techniques used throughout the data preparation process.Learn to clean inconsistent datasets, engineer meaningful features, and automate preparation pipelines using Pandas, NumPy, and Scikit Learn. Every chapter is designed to help you move from raw data to model ready datasets with greater speed, accuracy, and confidence.Build cleaner datasets and reduce data preparation time through repeatable workflowsMaster feature creation, transformation, encoding, scaling, and dimensionality reduction techniquesDevelop production ready data preparation pipelines that improve scalability and maintainabilityWritten for data scientists, machine learning engineers, analysts, developers, and technical professionals who need reliable feature engineering solutions in real world environments. Based on practical implementation experience and industry standard workflows used in modern data science projects.You'll gain the exact techniques needed to prepare high quality data before poor feature design undermines your results This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Zustand: new. Paperback. Stop fragile feature engineering workflows before they create inconsistent models, unreliable predictions, and costly deployment failures. Fix feature engineering challenges in your machine learning projects without relying on disconnected scripts, manual preprocessing, or hard to maintain workflows. This book gives you a practical implementation guide for building production ready feature engineering systems that scale from development to deployment not toy examples or theory heavy discussions. Learn to design automated pipelines, manage feature transformations consistently, and deploy reliable preprocessing frameworks using industry standard Python tools and proven engineering practices. Build reusable feature engineering pipelines that reduce development time and improve model consistency. Master production-focused workflows, automation strategies, and deployment ready preprocessing systems. Create scalable feature management solutions that support real world machine learning applications. Written for data scientists, machine learning engineers, AI developers, analytics professionals, and technical practitioners who need reliable feature engineering workflows in production environments. Based on practical implementation patterns, deployment challenges, and real world machine learning system design. You'll get exact techniques to automate feature engineering workflows, maintain data consistency, and deploy scalable preprocessing systems before small issues become production emergencies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…