Inside explore the Spark machine learning

Explore the technology that is changing our world!Imagine a machine that can learn from experience and teach itself new things - that's AI in action! Trace the development of intelligent machines fr

Inside the Money Machine is poetry for the immense majority for those who work for a living, out of the house or at home, from the laundromat to the classroom, from blue-collar construction sites to w

Core Insight：Cross-Domain Data Collaboration: Unlocking Chip PotentialEliminating the "efficiency gap" caused by knowledge silos is the starting point for industry potential. Data doesn't lie; Data Science provides the solution: Through innovation and cross-domain restructuring, we visualize results to become the critical accelerator for boosting efficiency.GenAI Reshaping the Future of SemiconductorsFacing the immense challenge of the slowing pace of Moore's Law, the semiconductor industry urgently requires new breakthroughs. This book is specifically designed to solve the "Efficiency Black Hole" that consumes tens of billions of dollars annually in the industry.The Empowering DTCO Innovation with AI and Machine Learning offers readers a practical DTCO.ML Framework, demonstrating how to leverage Machine Learning (ML) and Generative AI (GenAI) technologies to inject new acceleration into chip manufacturing processes. Learn to master process variability and optimize chip energy efficien

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the ne

Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design mod

Machine Learning with Spark and Python Essential Techniques for Predictive Analytics Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves

This book covers machine learning, one of the hottest topics in more recent years. With computing power increasing exponentially and costs decreasing at the same time, there is no better time for mach

Written by leading researchers, this complete introduction brings together all the theory and tools needed for building robust machine learning in adversarial environments. Discover how machine learning systems can adapt when an adversary actively poisons data to manipulate statistical inference, learn the latest practical techniques for investigating system security and performing robust data analysis, and gain insight into new approaches for designing effective countermeasures against the latest wave of cyber-attacks. Privacy-preserving mechanisms and the near-optimal evasion of classifiers are discussed in detail, and in-depth case studies on email spam and network security highlight successful attacks on traditional machine learning algorithms. Providing a thorough overview of the current state of the art in the field, and possible future directions, this groundbreaking work is essential reading for researchers, practitioners and students in computer security and machine learning,

Over the last two decades a new type of hit song has emerged, one that is almost inescapably catchy. Pop songs have always had a "hook," but today’s songs bristle with them: a hook every sev

Explore the web and make smarter predictions using Python About This Book * Targets two big and prominent markets where sophisticated web apps are of need and importance. * Practical examples of build

From the jungles of the trading floor to the casinos of Las Vegas, The Big Short, Michael Lewis's No.1 bestseller, tells the outrageous story of the misfits, renegades and visionaries who saw that the

The real story of the crash began in bizarre feeder markets where the sun doesn't shine and the SEC doesn't dare, or bother, to tread: the bond and real estate derivative markets where geeks invent im

Over the last two decades a new type of song has emerged. Today’s hits bristle with “hooks,” musical burrs designed to snag your ear every seven seconds. Painstakingly crafted to tweak the brain’s del

In this riveting anatomy of authoritarianism, acclaimed journalist William Dobson takes us inside the battle between dictators and those who would challenge their rule. Recent history has seen an incr

The real story of the crash began in bizarre feeder markets where the sun doesn't shine and the SEC doesn't dare, or bother, to tread: the bond and real estate derivative markets where geeks invent im

'We fed the monster until it blew up …' While Wall Street was busy creating the biggest credit bubble of all time, a few renegade investors saw it was about to burst, bet against the banking system -

Truth really is stranger than fiction. Who better than the author of the signature bestseller Liar's Poker to explain how the event we were told was impossible--the free fall of the American economy--