Department of Computer Science and Engineering’s Chen co-authors book

Zhiqian Chen

Zhiqian Chen, an assistant professor in the Department of Computer Science and Engineering, co-authored Machine Learning for Computer Scientists and Data Analysts—From an Applied Perspective.

The book, co-authored by Zhiqian Chen, Setareh Rafatirad, Houman Homayoun and Sai Manoj Pudukotai Dinakarrao, is a comprehensive guide that introduces readers to the theoretical aspects of machine learning (ML) algorithms. It starts from simple neuron basics and progresses to complex neural networks, including generative adversarial neural networks and graph convolution networks. The book not only helps readers understand the concepts of ML algorithms but also equips them with the skills necessary to choose an apt ML algorithm for a problem they wish to solve. It engages readers with numerous case studies, spanning from simple time-series forecasting to object recognition and recommender systems using massive databases. The book provides practical implementation examples and assignments, intriguing readers to practice and improve their programming capabilities for ML applications.

Machine Learning for Computer Scientists and Data Analysts—From an Applied Perspective was published by Springer Nature and is available in print of ebook.