Description
Dive into the fascinating world of inductive reasoning, where inference, learning, and discovery shape human understanding. In Induction: Processes of Inference, Learning & Discovery, John Holland and his co-authors explore the cognitive and computational mechanisms behind pattern recognition, scientific discovery, and machine learning. This book is ideal for students, researchers, and professionals in AI, cognitive science, and psychology.
You Will Learn
- The fundamentals of inductive reasoning and its role in learning.
- How humans and machines identify patterns and form hypotheses.
- The connection between scientific discovery and cognitive processes.
- Computational models of inference and their applications.
- How induction shapes problem-solving in AI and real-world scenarios.
Specification: Induction Processes of Inference, Learning & Discovery (English)
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Induction Processes of Inference, Learning & Discovery (English)
Original price was: $1.80.$0.24Current price is: $0.24.
Karan Bhatia –
One of the best books on learning and inference. If you’re curious about how knowledge is formed, this book is a great place to start.
Sonal Jha –
A detailed analysis of inference and discovery processes. It provides a strong intellectual framework for understanding human reasoning.
Amitabh Das –
A well-researched book that lays the foundation for understanding human and machine learning. A must-read for AI professionals.
Shruti Nambiar –
Holland masterfully explains the learning process through induction. His writing is engaging, though certain chapters require careful reading.
Rahul Gupta –
A great read for those interested in knowledge representation, AI, and machine learning. The book provides a strong theoretical foundation.
Ishita Bose –
An informative book that bridges cognitive science and artificial intelligence. Some sections are technical but very rewarding.
Suresh Patil –
A deep and insightful read on the process of learning and discovery. Holland’s theories are well supported by real-world examples.
Pooja Dutta –
A fascinating book on how we derive meaning from patterns. The discussions on machine learning applications are particularly interesting.
Nikhil Menon –
Holland provides a well-structured and in-depth look at inductive reasoning. A valuable book for students and professionals alike.
Tanya Bhatt –
The book explains how inference works in both humans and machines. It’s a crucial read for those studying AI and cognitive science.
Arjun Saxena –
A brilliant work that connects logic, learning, and scientific discovery. Some sections are complex, but the book is worth the effort.
Deepa Kulkarni –
An essential book for understanding how we form conclusions based on incomplete data. This is a great resource for academics and professionals alike.
Manish Verma –
Holland presents induction as the key to discovery. His writing is clear, and the examples help in understanding complex concepts.
Ananya Banerjee –
A thought-provoking book that explains how we process patterns and make discoveries. This is a must-read for anyone in research fields.
Rajiv Pillai –
Holland presents a structured approach to understanding inference and learning. A solid read for anyone exploring knowledge acquisition.
Simran Kapoor –
A deep dive into learning and discovery processes. Some parts are quite theoretical, but the book is filled with valuable insights.
Aditya Malhotra –
A comprehensive book on inductive reasoning, blending psychology, computer science, and philosophy. Highly recommended!
Neha Choudhary –
The book presents induction as the backbone of human and artificial intelligence. It’s an eye-opening read for anyone in cognitive psychology.
Vikram Joshi –
Holland does an excellent job explaining how we derive new knowledge from existing patterns. A must-read for AI and ML enthusiasts.
Kavita Reddy –
This book explains the foundation of reasoning and discovery. It’s an intellectual treat for those interested in philosophy and cognitive science.