- -42%
Deep Learning: Foundations and Concepts by Christopher M. Bishop
0Original price was: $89.99.$52.00Current price is: $52.00.This textbook teaches the mathematics and concepts behind deep learning, not just how to use the tools.
Christopher M. Bishop, author of Pattern Recognition and Machine Learning, and Hugh Bishop cover neural networks, Transformers and LLMs, Graph Neural Networks, and generative models including VAEs, GANs, and diffusion models, with a Bayesian approach to uncertainty throughout. It is written for students, researchers, and practitioners in AI. ISBN 9783031454677.
- -22%
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
0Original price was: $59.99.$46.90Current price is: $46.90.Designing Data-Intensive Applications, by Martin Kleppmann, is a vendor-neutral guide to the concepts behind modern data systems, published by O’Reilly.
It works through relational databases, NoSQL datastores, message brokers and stream processors, along with the distributed systems trade-offs in replication, partitioning, transactions and consistency models. It suits software engineers and architects building data-heavy systems. ISBN 9781449373320.
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Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data
0Original price was: $79.99.$42.90Current price is: $42.90.A hands-on guide to unsupervised learning that builds working models from unlabeled data.
Ankur A. Patel uses Scikit-learn and TensorFlow with Keras to walk through clustering, dimensionality reduction and anomaly detection with step-by-step code. It suits developers and data scientists ready to move past supervised learning. ISBN 9781492035640.
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, 2nd Edition
0Original price was: $79.99.$45.00Current price is: $45.00.Fifty-plus statistical concepts data scientists actually use, with code in R and Python.
Peter Bruce, Andrew Bruce and Peter Gedeck skip dense proofs for practical, code-driven explanations covering exploratory analysis, regression and machine learning techniques. It suits working data scientists and analysts who want application over theory. ISBN 9781492072942.
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Reinforcement Learning: An Introduction (2nd Edition)
0Original price was: $120.00.$51.90Current price is: $51.90.The book that defined how a generation learned reinforcement learning, expanded and updated in its second edition.
Sutton and Barto’s Reinforcement Learning: An Introduction gives a clear, unhurried account of how an agent learns to act by maximising reward while interacting with a complex, uncertain environment. Part I develops the tabular case, where exact solutions exist, and Part II moves to function approximation and the methods that scale to real problems. MIT Press hardcover, ISBN 9780262039246.
