Statistical Modeling in Machine Learning: Concepts and Applications

Statistical Modeling in Machine Learning: Concepts and Applications presents the basic concepts and roles of statistics, exploratory data analysis and machine learning. The various aspects of Machine Learning are discussed along with basics of statistics. Concepts are presented with simple examples and graphical representation for better understanding of techniques. This book takes a holistic approach - putting key concepts together with an in-depth treatise on multi-disciplinary applications of machine learning. New case studies and research problem statements are discussed, which will help researchers in their application areas based on the concepts of statistics and machine learning. Statistical Modeling in Machine Learning: Concepts and Applications will help statisticians, machine learning practitioners and programmers solving various tasks such as classification, regression, clustering, forecasting, recommending and more. Provides a comprehensive overview of the state-of-the-art in statistical concepts applied to Machine Learning with the help of real-life problems, applications and tutorials Presents a step-by-step approach from fundamentals to advanced techniques Includes Case Studies with both successful and unsuccessful applications of Machine Learning to understand challenges in its implementation, along with worked examples INDICE: SECTION A: Introduction and Theoretical Background1. Introduction to Statistics2. Statistics in Data Preparation and Pre-processing3. Statistics for Model Evaluation4. Classification Problems inMachine Learning5. RegressionTasks inMachine Learning6. Unsupervised MachineLearningand ClusteringTasks7. Model Selection 8. Statistics Exploratory Data Analysis for Prediction 9. Time Series Forecasting with Machine Learning  10. Multivariate Real-time Prediction with Machine LearningSECTION B11. Prediction in Social Science Domain12. Predictionin HealthEconomicsDomain13. Prediction in Finance Domain14. Case Study: Prediction in Environmental Science Domain15. Case Study: Prediction in Education Domain16. Case Study: Prediction in Medical Domain17. Conclusion and Future Work

• ISBN: 978-0-323-91776-6
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 400
• Fecha Publicación: 01/11/2022
• Nº Volúmenes: 1
• Idioma: Inglés