Description
Book SynopsisThis book describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalise these strategies. The book will benefit information professionals, programmers, consultants, professors, students, and industry experts who seek a variety of real-world illustrations with an implementation based on machine learning algorithms.
Table of ContentsPreface; Acknowledgements; Introduction; Deep Learning; Convolutional Neural Networks; Recurrent Neural Networks; Ensemble Learning; Implementing DL and Ensemble Learning Models: Real World Use Cases; Appendix; Suggested Reading; About the Authors; Index.
