Machine Learning Mode Serving Patterns

This book describes the recent innovation of deep in-memory architectures for realizing AI systems that operate at the edge of energy-latency-accuracy trade-offs. From first principles to lab prototypes, this book provides a comprehensive view of this emerging topic for both the practicing engineer in industry and the researcher in academia. The book is a journey into the exciting world of AI systems in hardware.

This book focuses on both theory and applications in the broad areas of computational intelligence and machine learning.

This book constitutes selected papers from the First International Workshop on Deployable Machine Learning for Security Defense, MLHat 2020, held in August 2020. Due to the COVID-19 pandemic the conference was held online.

Unsupervised Machine Learning Clustering and Dimension Reduction Algorithms with Python Implementation and Applications

Interested in increasing your Machine Learning, Deep Learning expertise by effectively applying the mathematical skills? Then, this course is for you. With the growing learners of Machine Learning, Data Science, and Deep Learning.

Much of machine learning is built around the idea of loss functions and optimizing for them. To understand them, you first need to understand Calculus.

The Large Hadron Collider (LHC) is the largest data generation machine for the time being. It doesn’t produce the big data, the data is gigantic. Just one of the four experiments generates thousands gigabytes per second. The intensity of data flow is only going to be increased over the time. So the data processing techniques have to be quite sophisticated and unique. In this course we’ll introduce students into the main concepts of the Physics behind those data flow so the main puzzles of the Universe Physicists are seeking answers for will be much more transparent.

Machine Learning , Python, Advanced Data Visualization, R Programming, Linear Regression, Decision Trees, NumPy, Pandas.