MACHINE LEARNING
found 109 books
Efficient Learning Machines
by Mariette Awad, Rahul Khanna
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, cla...
Neural Networks and Deep Learning
by Charu C. Aggarwal
This book covers both classical and modern models in deep learning. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional mac...
Understanding Machine Learning
by Shai Shalev-Shwartz, Shai Ben-David
The subject of this book is automated learning, or, as we will more often call it, Machine Learning (ML). That is, we wish to program computers so that they can "learn" from input available to them. Roughly speaking, learning is the process of converting experience into expertise or knowledge. The input to a learning algorithm is training...
Deep Learning with JavaScript
by Shanqing Cai, Stanley Bileschi, Eric D. Nielsen, Francois Chollet
Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of t...
Representation Learning for Natural Language Processing
by Zhiyuan Liu, Yankai Lin, Maosong Sun
This open book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introdu...
Algorithmic Aspects of Machine Learning
by Ankur Moitra
This course is organized around algorithmic issues that arise in machine learning. Modern machine learning systems are often built on top of algorithms that do not have provable guarantees, and it is the subject of debate when and why they work. In this class, we focus on designing algorithms whose performance we can rigorously analyze for fundamen...
Entity-Oriented Search
by Krisztian Balog
This book covers all facets of entity-oriented search—where "search" can be interpreted in the broadest sense of information access—from a unified point of view, and provides a coherent and comprehensive overview of the state of the art. It represents the first synthesis of research in this broad and rapidly developing area. Selected ...
Disrupting Finance
by Theo Lynn, John G. Mooney, Pierangelo Rosati, Mark Cummins
This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase ag...
IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency
by Oliver Niggemann, Peter Schüller
This open access work presents selected results from the European research and innovation project IMPROVE which yielded novel data-based solutions to enhance machine reliability and efficiency in the fields of simulation and optimization, condition monitoring, alarm management, and quality prediction. Prof. Dr. Oliver Niggemann is Professor for Ar...
Projection-Based Clustering through Self-Organization and Swarm Intelligence
by Michael Christoph Thrun
It covers aspects of unsupervised machine learning used for knowledge discovery in data science and introduces a data-driven approach to cluster analysis, the Databionic swarm(DBS). DBS consists of the 3D landscape visualization and clustering of data. The 3D landscape enables 3D printing of high-dimensional data structures.The clustering and numbe...