IBM Machine Learning for Dummies

Livro digital

Título:
IBM Machine Learning for Dummies

Autor:
Daniel Kirsch, Judith Hurwitz

Categoria:
Tecnologia > IA

Doador:
Raffaello D. N.

Sinopse:
Machine learning only becomes useful when it connects data, algorithms, and business decisions, and this guide opens by moving straight through that chain. Its structure starts with the fundamentals of machine learning, then moves into applied strategy, looking inside the machine learning cycle, and getting started with practical projects before ending with skills and business solutions. That progression gives the reader a clear map from concept to action. The book covers supervised, unsupervised, and reinforcement learning, then links those methods to predictive and descriptive analytics, data preparation, and model training. It also brings in hybrid cloud context, algorithm selection, collaboration across business and technical roles, and concrete use cases such as customer churn, fraud prevention, patient health, and IT operations. The result is a broad but accessible survey of how machine learning systems are actually used. As an IBM-branded For Dummies title, it is designed to make a complex field approachable without losing the practical business angle. Readers get a solid foundation in terminology, workflow, and real-world application, along with a useful view of where machine learning fits inside modern organizations and why data quality and teamwork matter so much.