The new edition of this popular professional book on artificial intelligence (ML) and machine learning (ML) has been revised for classroom or training use.
This textbook presents methods and techniques for time series analysis and forecasting and shows how to use Python to implement them and solve data science problems.
The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial... Læs mere
Machine Learning Toolbox for Social Scientists covers predictive methods with complementary statistical "tools" that make it mostly self-contained. The inferential statistics is the traditional framework for most data analytics courses in social science and business fields.
This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine... Læs mere
An accessible text that provides students and instructors with the data science foundations to address earth science questions using real-world case studies. Focusing on... Læs mere
This book provides a comprehensive introduction to the theory of tensor network renormalization for the first time. An accessible primer for scientists and engineers, this book would also be ideal as a reference text for a graduate course in this area.
Human Rights and Artificial Intelligence is a seminal text on the legal ramifications of machine learning. Analysing both the concept of human rights and... Læs mere
The concept of deep machine learning is easier to understand by paying attention to the cyclic stochastic time series and a time series whose content is non-stationary not only within the cycles, but also over the cycles as the cycle-to-cycle variations.
Machine learning (ML) is progressively reshaping the fields of quantitative finance and algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers, notably for alpha signal generation and stocks selection.
This book addresses the growing need for machine learning and data mining in neuroscience. The book is replete with fully working machine learning code. It also contains lab assignments and quizzes, making it appropriate for use as a textbook.