This book provides:End to end design of the most popular Machine Learning system at big tech companies.Most common Machine Learning …
This book provides a novel framework for understanding and revising labor markets and education policies in an era of machine …
""Discover the power of Machine Learning, Neural, and Statistical Classification with this comprehensive guide written by esteemed author Michie D. …
Handling inherent uncertainty and exploiting compositional structure are fundamental to understanding and designing large-scale systems. Statistical relational learning builds on …
Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are …
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive …
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine …
Implement machine learning pipelines with Google Cloud Vertex AI Key Features Understand the role of an AI platform and MLOps …
Explore powerful R packages to create predictive models using ensemble methodsKey FeaturesImplement machine learning algorithms to build ensemble-efficient modelsExplore powerful …
For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the …
Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical …
This book describes the theory, operation, and application of genetic algorithms-search algorithms based on the mechanics of natural selection and …
I have no idea how this is marketed as a college level text on the subject. It is just a …
Mining big data requires a deep investment in people and time. How can you be sure youre building the right …
with bonus article "Why Every Company Needs an Augmented Reality Strategy" by Michael E. Porter and James E. Heppelmann
Adversarial Robustness for Machine Learning summarizes the recent progress on this topic and introduces popular algorithms on adversarial attack, defense …
