English | 2021 | ISBN: 0262542099 | 175 pages | True PDF | 3.22 MB
Experts from disciplines that range from computer science to philosophy consider the challenges of building AI systems that humans can trust.

Read More: Machines We Trust Perspectives on Dependable AI (The MIT Press) [True PDF]

English | 2021 | ISBN: 1800567030 | 763 pages | True PDF EPUB | 61.2 MB
A step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker

Read More: Machine Learning with Amazon SageMaker Cookbook 80 proven recipes for data scientists and developers

English | 2021 | ISBN: 0367618907 | 389 pages | pdf | 20.68 MB
The signal processing (SP) landscape has been enriched by recent advances in artificial intelligence (AI) and machine learning (ML), yielding new tools for signal estimation, classification, prediction, and manipulation. Layered signal representations, nonlinear function approximation and nonlinear signal prediction are now feasible at very large scale in both dimensionality and data size. These are leading to significant performance gains in a variety of long-standing problem domains like speech and image analysis as well as providing the ability to construct new classes of nonlinear functions (e.g., fusion, nonlinear filtering).

Read More: Machine Learning in Signal Processing Applications, Challenges, and Road Ahead

English | 2021 | ISBN: 1801819629 | 371 pages | True (PDF EPUB) | 29.43 MB
Become proficient in deriving insights from time-series data and analyzing a model's performance

Read More: Machine Learning for Time-Series with Python Forecast, predict and detect anomalies with state-of-the-art machine learning

English | 2021 | ISBN: 0367626489 , 978-0367622565 | 199 pages | True PDF | 28.87 MB
Cloud computing offers subscription-based on-demand services, and it has emerged as the backbone of the computing industry. It has enabled us to share resources among multiple users through virtualization, which creates a virtual instance of a computer system running in an abstracted hardware layer. Unlike early distributed computing models, it offers virtually limitless computing resources through its large scale cloud data centers. It has gained wide popularity over the past few years, with an ever-increasing infrastructure, a number of users, and the amount of hosted data. The large and complex workloads hosted on these data centers introduce many challenges, including resource utilization, power consumption, scalability, and operational cost. Therefore, an effective resource management scheme is essential to achieve operational efficiency with improved elasticity. Machine learning enabled solutions are the best fit to address these issues as they can analyze and learn from the data. Moreover, it brings automation to the solutions, which is an essential factor in dealing with large distributed systems in the cloud paradigm.

Read More: Machine Learning for Cloud Management

English | 2021 | ISBN: 1032047232 | 243 pages | True PDF | 23.89 MB
The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications.　 It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects.

Read More: Machine Learning and IoT for Intelligent Systems and Smart Applications

English | 2021 | ISBN: 1801079250 | 277 pages | True (PDF EPUB) | 32.14 MB
Supercharge the value of your machine learning models by building scalable and robust solutions that can serve them in production environments

Read More: Machine Learning Engineering with Python Manage the production life cycle of machine learning models

English | 2021 | ISBN: 1617296813 | 855 pages | True EPUB, MOBI | 30.35 MB
Time to flex your machine learning muscles! Take on the carefully designed challenges of theMachine Learning Bookcampand master essential ML techniques through practical application.

Read More: Machine Learning Bookcamp Build a portfolio of real-life projects (True EPUB, MOBI)

English | 2021 | ISBN: 1617296813 , 978-1617296819 | 473 pages | True PDF | 40.02 MB
Time to flex your machine learning muscles! Take on the carefully designed challenges of theMachine Learning Bookcampand master essential ML techniques through practical application.

Read More: Machine Learning Bookcamp Build a portfolio of real-life projects (Final release)

English | 2021 | ISBN: 0262542528 | 282 pages | True PDF | 7.97 MB
A concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.

Read More: Machine Learning (The MIT Press Essential Knowledge), Revised and Updated Edition (True PDF)