Multivariate Analysis and Machine Learning Techniques

Angebote / Angebote:

This book covers multivariate analysis and other computational techniques for solving data analytics problems using Python. The topics covered in the book consist: of (a) a working introduction to programming with Python for data analytics, (b) a comprehensive overview of important statistical techniques-probability, hypothesis testing, correlation and regression, factor analysis, classification techniques-logit, linear discriminant analysis, decision tree, support vector machines, clustering techniques, and survival analysis, and (c) introduction to other computational techniques such as market basket analysis, graph theory, and machine learning techniques. This book has a collection of 150 tutorials and worked-out exercises for solving problems using statistical and computational techniques using the programming language Python. This book comes in handy as it provides worked-out examples that conceptualize real-world problems using data curated from popular databases. The book provides a jump start for a self-learning analytics student, a beginner in statistics, or someone new to programming in Python. The book is used as a supplementary academic textbook for analytics students for courses on statistics, multivariate analysis, data mining, and business analytics. The book is also used as a reference handbook by a business analytics professional.