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Machine Learning Systems

Machine learning applications autonomously reason about data at massive scale. It's important that they remain responsive in the face;

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Machine Learning and Systems Engineering

A large international conference on Advances in Machine Learning and Systems Engineering was held in UC Berkeley, California, USA, October;

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Building Machine Learning Systems with Python

Get more from your data by creating practical machine learning systems with Python Key Features Develop your own Python-based machine;

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Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth;

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Machine Learning for Cyber Physical Systems

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers;

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Machine Learning for Cyber Physical Systems

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers;

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Mastering Machine Learning for Penetration Testing

Become a master at penetration testing using machine learning with Python Key Features Identify ambiguities and breach intelligent security;

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Machine Learning for Cyber Physical Systems

This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains;

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Human-in-the-Loop Machine Learning

Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus;

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Advances in Machine Learning Applications in Software Engineering

Machine learning is the study of building computer programs that improve their performance through experience. To meet the challenge;

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Machine Learning in Healthcare

Machine Learning in Healthcare discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. It;

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Designing Machine Learning Systems with Python

Design efficient machine learning systems that give you more accurate results About This Book * Gain an understanding of the machine;

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Machine Learning for Predictive Analysis

This book gathers papers addressing state-of-the-art research in the areas of machine learning and predictive analysis, presented virtually;

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Knowledge Acquisition and Machine Learning

For graduate-/research- level students and professors, this book integrates machine learning with knowledge acquisition to overcome the;

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Computational Trust Models and Machine Learning

Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various;

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Deep Learning with TensorFlow 2 and Keras

Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key;

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Applied Recommender Systems with Python

This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an;

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Applied Recommender Systems with Python

This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an;

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Machine Learning with Python for Everyone

The Complete Beginner's Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for;

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Intelligent Learning Systems

Intelligent (machine) learning is a subfield of artificial intelligence and it originates from the researches in the pattern recognition;

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Machine Learning for Energy Systems

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Distributed Machine Learning and Gradient Optimization

This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the;

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Handbook of Research on Machine Learning Innovations and Trends

Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications;

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Machine Learning

Machine Learning: Concepts, Methodologies, Tools, and Applications offers a wide-ranging selection of key research in a complex field;

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Computational Learning Theory & Natural Learning Systems V 2 - Intersections Between Theory & Experiment

This second volume defines possible areas of joint research in artificial intelligence and machine learning. It uses knowledge from the;

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Machine Learning with PySpark

Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business;

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Building Intelligent Systems

Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and;

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