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The Writing Machine A History of the Typewriter

The Writing Machine A History of the Typewriter

First Published in 1973 The Writing Machine presents a comprehensive history of the typewriter. Michael Adler not only investigated the history of the machine but also started collecting typewriters because of the difficulty of discovering what these old machines looked like. Then he found there were other collectors all over the world who supplied him with such a wealth of data that he had eventually to limit the scope of his ‘history’. There are hundreds and hundreds of makes and models of ‘conventional’ front-stroke type bar machines with four-row keyboards but they were virtually all the same. It is the unconventional ones that are interesting and it is on these that the author concentrates. The book is amusing as well as informative and it ends with a complete catalogue of ‘unconventional’ typewriters manufactured up to the 1930s when the ‘conventional’ machine had become universal. This book is a must read for anyone interested to learn about the writing machine. | The Writing Machine A History of the Typewriter

GBP 105.00
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Machine Learning Concepts Techniques and Applications

Machine Learning Concepts Techniques and Applications

Machine Learning: Concepts Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases self-assessments exercises activities numerical problems and projects associated with each chapter aims to concretize the understanding. Features Concepts of Machine learning from basics to algorithms to implementation Comparison of Different Machine Learning Algorithms – When to use them & Why – for Application developers and Researchers Machine Learning from an Application Perspective – General & Machine learning for Healthcare Education Business Engineering Applications Ethics of machine learning including Bias Fairness Trust Responsibility Basics of Deep learning important deep learning models and applications Plenty of objective questions Use Cases Activity and Project based Learning Exercises The book aims to make the thinking of applications and problems in terms of machine learning possible for graduate students researchers and professionals so that they can formulate the problems prepare data decide features select appropriate machine learning algorithms and do appropriate performance evaluation. | Machine Learning Concepts Techniques and Applications

GBP 140.00
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Indoor Body Health & Fitness Adjustable Magnetic Rowing Machine Rower with LCD Digital Monitor & Wheels for Home, Office, Gym - Life Essentials

Indoor Body Health & Fitness Adjustable Magnetic Rowing Machine Rower with LCD Digital Monitor & Wheels for Home, Office, Gym - Life Essentials

Row into shape with this quality design Magnetic Rowing Machine from. The Magnetic Rowing Machine is designed for convenience while also providing the challenging feel of outdoor rowing. Build with smoother and quieter magnetic tension system with 8 levels of adjustable tension, convenient large LCD console, fully padded seat, larger anti-slip foot pedals, and foldable design for easy storage. Enjoy the fitness at home or office.

GBP 139.39
2

Applied Machine Learning for Smart Data Analysis

Applied Machine Learning for Smart Data Analysis

The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are used in heterogeneous IoT environments have been discussed including interpretation context awareness analyzing various data sources machine learning algorithms and intelligent services and applications. Further it includes unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections such as machine learning security IoT and data mining the concepts are explained with practical implementation including results. Key Features Follows an algorithmic approach for data analysis in machine learning Introduces machine learning methods in applications Address the emerging issues in computing such as deep learning machine learning Internet of Things and data analytics Focuses on machine learning techniques namely unsupervised and semi-supervised for unseen and seen data sets Case studies are covered relating to human health transportation and Internet applications | Applied Machine Learning for Smart Data Analysis

GBP 125.00
1

Machine Learning Theory and Practice

Machine Learning Theory and Practice

Machine Learning: Theory and Practice provides an introduction to the most popular methods in machine learning. The book covers regression including regularization tree-based methods including Random Forests and Boosted Trees Artificial Neural Networks including Convolutional Neural Networks (CNNs) reinforcement learning and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid illustrated with figures and examples. For each machine learning method discussed the book presents appropriate libraries in the R programming language along with programming examples. Features: Provides an easy-to-read presentation of commonly used machine learning algorithms in a manner suitable for advanced undergraduate or beginning graduate students and mathematically and/or programming-oriented individuals who want to learn machine learning on their own. Covers mathematical details of the machine learning algorithms discussed to ensure firm understanding enabling further exploration Presents worked out suitable programming examples thus ensuring conceptual theoretical and practical understanding of the machine learning methods. This book is aimed primarily at introducing essential topics in Machine Learning to advanced undergraduates and beginning graduate students. The number of topics has been kept deliberately small so that it can all be covered in a semester or a quarter. The topics are covered in depth within limits of what can be taught in a short period of time. Thus the book can provide foundations that will empower a student to read advanced books and research papers. | Machine Learning Theory and Practice

GBP 110.00
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