Smarter Homes: How Technology Will Change Your Home Life
By 作者: Alexandra Deschamps-Sonsino
ISBN-10 书号: 148423362X
ISBN-13 书号: 9781484233627
Edition 版本: 1st ed.
Release Finelybook 出版日期: 2018-09-26
pages 页数: (168 )

$32.99

Book Description to Finelybook sorting
Examine the history of smart homes, how technology shapes our lives, and ways you can think about the home when developing new products. This book presents the opportunities in the homespace that will come from understanding the history and multiple players that have contributed to the development of the home in general.
You’ll start by breaking down the historical, societal and political context for the changes in focus of that ‘smartness’ from affordability, efficiency, convenience to recently experimentation. The second half of the book then reviews what current developments tell us about what our homes will look like in the next 10 years through the lens of spaces, services, appliances and behaviours in our homes.
Over the past 100 years, the home has been a battleground for ideas of future living. Fueled by the electrification of cities, the move from the country to cities, post-war recovery and the development of the internet, the way we live at home (alone or with others) has changed beyond recognition.
Science fiction writing, the entertainment industry, art, and modern interior design and architecture movements have also contributed to defining our aspirations around a future and now more present and possible ‘smart’ home.
Smarter Homes looks at the many new and innovative products that are being developed in the consumer and industrial spaces with a copy-paste mindset based on following larger businesses, such as Amazon, Google and Apple.
What You’ll Learn
Understand the historical context for current smart home products
Review the social aspect of home product development
Discover new home technologies being developed and which ones are available now
Track the industry behaviors being leveraged and how they may affect longer term market trends for consumer products
Who This Book Is For
Everyone working in product design and development, in R&D or in trends research, as well as those interested in the IoT for the home. This book will also give product business owners ideas about what has been done before and and avenues for future development.
Front Matter
1. Everything Electric
2. Homes as Factories
3. Pleasure and Convenience
4. Digital Everything
5. Cheaper, Embedded and Invisible
6. Emerging Themes and Whats Next?
7. Conclusion Back Matter

TensorFlow Reinforcement Learning Quick Start Guide: Get up and running with training and deploying intelligent, self-learning agents using Python
By 作者: Kaushik Balakrishnan
ISBN-10 书号: 1789533589
ISBN-13 书号: 9781789533583
Release Finelybook 出版日期: 2019-03-30
pages 页数: (184 )

$24.99

Book Description to Finelybook sorting
Learn
Understand the theory and concepts behind modern Reinforcement Learning algorithms
Code state-of-the-art Reinforcement Learning algorithms with discrete or continuous actions
Develop Reinforcement Learning algorithms and apply them to training agents to play computer games
Explore DQN, DDQN, and Dueling architectures to play Atari’s Breakout using TensorFlow
Use A3C to play CartPole and LunarLander
Train an agent to drive a car autonomously in a simulator
About
Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving.

The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator.

By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems.

Features
Explore efficient Reinforcement Learning algorithms and code them using TensorFlow and Python
Train Reinforcement Learning agents for problems, ranging from computer games to autonomous driving.
Formulate and devise selective algorithms and techniques in your applications in no time.

contents
1 Up and Running with Reinforcement Learning
2 Temporal Difference, SARSA, and Q-Learning
3 Deep Q-Network
4 Double DQN, Dueling Architectures, and Rainbow
5 Deep Deterministic Policy Gradient
6 Asynchronous Methods – A3C and A2C
7 Trust Region Policy Optimization and Proximal Policy Optimization
8 Deep RL Applied to Autonomous Driving

Cohesive Subgraph Computation over Large Sparse Graphs: Algorithms, Data Structures, and Programming Techniques (Springer Series in the Data Sciences)
By 作者: Lijun Chang – Lu Qin
ISBN-10 书号: 3030035980
ISBN-13 书号: 9783030035983
Edition 版本: 1st ed. 2018
Release Finelybook 出版日期: 2018-12-25
pages 页数: (107 )

$109.99

Book Description to Finelybook sorting
This book is considered the first extended survey on algorithms and techniques for efficient cohesive subgraph computation. With rapid development of information technology, huge volumes of graph data are accumulated. An availability of rich graph data not only brings great opportunities for realizing big values of data to serve key applications, but also brings great challenges in computation. Using a consistent terminology, the book gives an excellent introduction to the models and algorithms for the problem of cohesive subgraph computation. The materials of this book are well organized from introductory content to more advanced topics while also providing well-designed source codes for most algorithms described in the book.
This is a timely book for researchers who are interested in this topic and efficient data structure design for large sparse graph processing. It is also a guideline book for new researchers to get to know the area of cohesive subgraph computation.

Front Matter
1.Introduction
2.Linear Heap Data Structures
3.Minimum Degree-Based Core Decomposition
4.Average Degree-Based Densest Subgraph Computation
5.Higher-Order Structure-Based Graph Decomposition
6.Edge Connectivity-Based Graph Decomposition

Python for Signal Processing: Featuring IPython Notebooks
By 作者: José Unpingco
ISBN-10 书号: 3319013416
ISBN-13 书号: 9783319013411
Edition 版本: 2014
Release Finelybook 出版日期: 2013-10-05
pages 页数: (128 )

$139.99

Book Description to Finelybook sorting
This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.

Contents

Chapter 1 Introduction
Chapter 2 Sampling Theorem
Chapter 3 Discrete-Time Fourier Transform
Chapter 4 Introducing Spectral Analysis
Chapter 5 Finite Impulse Response Filters
Erratum
References
Symbols
Index

Android things Projects

By 作者: Francesco Azzola
ISBN-10 书号: 1787289249
ISBN-13 书号: 9781787289246
Release Finelybook 出版日期: 2017-07-06
pages 页数: 239

$39.99

Book Description to Finelybook sorting

Key Features
Learn to build promising IoT projects with Android Things
Make the most out of hardware peripherals using standard Android APIs
Build enticing projects on IoT, home automation, and robotics by leveraging Raspberry Pi 3 and Intel Edison

Book Description to Finelybook sorting
Android Things makes developing connected embedded devices easy by providing the same Android development tools, best-in-class Android framework, and Google APIs that make developers successful on mobile.
With this book, you will be able to take advantage of the new Android framework APIs to securely build projects using low-level components such as sensors, resistors, capacitors, and display controllers. This book will teach you all you need to know about working with Android Things through practical projects based on home automation, robotics, IoT, and so on. We’ll teach you to make the most of the Android Things and build enticing projects such as a smart greenhouse that controls the climate and environment automatically. You’ll also create an alarm system, integrate Android Things with IoT cloud platforms, and more.
By the end of this book, you will know everything about Android Things, and you’ll have built some very cool projects using the latest technology that is driving the adoption of IoT. You will also have primed your mindset so that you can use your knowledge for profitable, practical projects.
What you will learn
Understand IoT ecosystem and the Android Things role
See the Android Things framework: installation, environment, SDK, and APIs
See how to effectively use sensors (GPIO and I2C Bus)
Integrate Android Things with IoT cloud platforms
Create practical IoT projects using Android Things
Integrate Android Things with other systems using standard IoT protocols
Use Android Things in IoT projects
About the Author
Francesco Azzola is an electronic engineer with over 15 years of experience in computer programming and JEE architecture. He is SCEA certified (Sun Certified Enterprise Architect), SCWCD, and SCJP. He is an Android and IoT enthusiast. He loves creating IoT projects using Arduino, Raspberry Pi, Android, and other platforms.
He is interested in the convergence between IoT and mobile applications. Previously, he worked in the mobile development field for several years. He has created a blog called survivingwithandroid,where he shares posts about coding in Android and IoT projects.
Contents
Chapter 1. Getting Started with Android Things
Chapter 2. Create an alarm system using Android Things
Chapter 3. How to make an environmental monitoring system
Chapter 4. Integrate Android Things with IoT cloud platforms
Chapter 5. Create a smart system to control ambient light
Chapter 6. Remote Weather station
Chapter 7. Build a spying eye
Chapter 8. Android with Android Things

Design and Analysis of Algorithms: A Contemporary Perspective
By 作者: Sandeep Sen – Amit Kumar
ISBN-10 书号: 1108721990
ISBN-13 书号: 9781108721998
Release Finelybook 出版日期: 2019-07-31
pages 页数: (350 )

$64.99
The text covers important algorithm design techniques, such as greedy algorithms, dynamic programming, and divide-and-conquer, and gives applications to contemporary problems. Techniques including Fast Fourier transform, KMP algorithm for string matching, CYK algorithm for context free parsing and gradient descent for convex function minimization are discussed in detail. The book’s emphasis is on computational models and their effect on algorithm design. It gives insights into algorithm design techniques in parallel, streaming and memory hierarchy computational models. The book also emphasizes the role of randomization in algorithm design, and gives numerous applications ranging from data-structures such as skip-lists to dimensionality reduction methods.
Content
Figures
Tables
Preface
Acknowledgments
1Model and Analysis
2Basics of Probability and Tail Inequalities
3 Warm-up Problems
4 Optimization l:Brute Force and Greedy Strategy
5 Optimization I:Dynamic Programming
6 Searching
7 Multidimensional Searching and Geometric Algorithms
8 String Matching and Finger Printing
9 Fast Fourier Transform and Applications
10 Graph Algorithms
11 Maximum Flow and Applications
12NP Completeness and Approximation Algorithms
13 Dimensionality Reduction
14 Parallel Algorithms
15 Memory Hierarchy and Caching
16Streaming Data Model

Data Visualization with Python: Create an impact with meaningful data insights using interactive and engaging visuals
By 作者: Mario Döbler – Tim Größmann
ISBN-10 书号: 1789956463
ISBN-13 书号: 9781789956467
Release Finelybook 出版日期: 2019-02-28
pages 页数: (368 )

$34.99

Book Description to Finelybook sorting
Data Visualization with Python reviews the spectrum of data visualization and its importance. Designed for beginners, it’ll help you learn about statistics by computing mean, median, and variance for certain numbers.

In the first few chapters, you’ll be able to take a quick tour of key NumPy and Pandas techniques, which include indexing, slicing, iterating, filtering, and grouping. The book keeps pace with your learning needs, introducing you to various visualization libraries. As you work through chapters on Matplotlib and Seaborn, you’ll discover how to create visualizations in an easier way. After a lesson on these concepts, you can then brush up on advanced visualization techniques like geoplots and interactive plots.

You’ll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful visualizations. What’s more? You’ll study how to plot geospatial data on a map using Choropleth plot and understand the basics of Bokeh, extending plots by adding widgets and animating the display of information.

By the end of this book, you’ll be able to put your learning into practice with an engaging activity, where you can work with a new dataset to create an insightful capstone visualization.

Contents
1: THE IMPORTANCE OF DATA VISUALIZATION AND DATA EXPLORATION
2: ALL YOU NEED TO KNOW ABOUT PLOTS
3: A DEEP DIVE INTO MATPLOTLIB
4: SIMPLIFYING VISUALIZATIONS USING SEABORN
5: PLOTTING GEOSPATIAL DATA
6: MAKING THINGS INTERACTIVE WITH BOKEH
7: COMBINING WHAT WE HAVE LEARNED
What You Will Learn
Understand and use various plot types with Python
Explore and work with different plotting libraries
Learn to create effective visualizations
Improve your Python data wrangling skills
Hone your skill set by using tools like Matplotlib, Seaborn, and Bokeh
Reinforce your knowledge of various data formats and representations
Authors
Mario Döbler
Mario Döbler is a Ph.D. student with focus in deep learning at the University of Stuttgart. He previously interned at the Bosch Center for Artificial Intelligence in Silicon Valley in the field of deep learning, using state-of-the-art algorithms to develop cutting-edge products. In his master thesis, he dedicated himself to apply deep learning to medical data to drive medical applications.

Tim Großmann
Tim Größmann is a CS student with an interest in diverse topics, ranging from AI to IoT. He previously worked at the Bosch Center for Artificial Intelligence in Silicon Valley, in the field of big data engineering. He’s highly involved in different open source projects and actively speaks at meetups and conferences about his projects and experiences.

Descriptive Data Mining (Computational Risk Management)
By 作者: David L. Olson – Georg Lauhoff
ISBN-10 书号: 9811371806
ISBN-13 书号: 9789811371806
Edition 版本: 2nd ed. 2019
Release Finelybook 出版日期: 2019-05-06
pages 页数: (130 )

$109.99

Book Description to Finelybook sorting
This book provides an overview of data mining methods demonstrated by software. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Diagnostic analytics can apply analysis to sensor input to direct control systems automatically. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on descriptive analytics.
The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis. Chapter 1 gives an overview in the context of knowledge management. Chapter 2 discusses some basic software support to data visualization. Chapter 3 covers fundamentals of market basket analysis, and Chapter 4 provides demonstration of RFM modeling, a basic marketing data mining tool. Chapter 5 demonstrates association rule mining. Chapter 6 is a more in-depth coverage of cluster analysis. Chapter 7 discusses link analysis.
Models are demonstrated using business related data. The style of the book is intended to be descriptive, seeking to explain how methods work, with some citations, but without deep scholarly reference. The data sets and software are all selected for widespread availability and access by any reader with computer links.

Drupal 8 Module Development: Build modules and themes using the latest version of Drupal 8, 2nd Edition
By 作者: Daniel Sipos
ISBN-10 书号: 1789612365
ISBN-13 书号: 9781789612363
Release Finelybook 出版日期: 2019-03-28
pages 页数: (580 )

$39.99

Book Description to Finelybook sorting
Learn to create and customize impressive Drupal 8 modules to extend your website’s functionalities
Drupal 8 comes with a release cycle that allows for new functionality to be added at a much faster pace. However, this also means code deprecations and changing architecture that you need to stay on top of. This book updates the first edition and includes the new functionality introduced in versions up to, and including 8.7.
The book will first introduce you to the Drupal 8 architecture and its subsystems before diving into creating your first module with basic functionality. You will work with the Drupal logging and mailing systems, learn how to output data using the theme layer and work with menus and links programmatically. Then, you will learn how to work with different kinds of data storages, create custom entities, field types and leverage the Database API for lower level database queries.
You will further see how to introduce JavaScript into your module, work with the various file systems and ensure the code you write works on multilingual sites. Finally, you will learn how to programmatically work with Views, write automated tests for your functionality and also write secure code in general.
By the end, you will have learned how to develop your own custom module that can provide complex business solutions. And who knows, maybe you’ll even contribute it back to the Drupal community.
Foreword by Dries Buytaert, founder of Drupal.
What you will learn

Develop Drupal 8 modules that do all the things you want
Master numerous Drupal 8 sub-systems and APIs in the process
Model, store, manipulate and process data to serve your purposes
Display data and content in a clean and secure way using the Drupal 8 theme system
Test your business logic to prevent regressions
Stay ahead of the curve and write code following the current best practices

contents
1 Developing for Drupal 8
2 Creating Your First Module
3 Logging and Mailing
4 Theming
5 Menus and Menu Links
6 Data Modeling and Storage
7 Your Own Custom Entity and Plugin Types
8 The Database API
9 Custom Fields
10 Access Control
11 Caching
12 JavaScript and the Ajax API
13 Internationalization and Languages
14 Batches, Queues, and Cron
15 Views
16 Working with Files and Images
17 Automated Testing
18 Drupal 8 Security

Getting Started with Python for the Internet of Things: Leverage the full potential of Python to prototype and build IoT projects using the Raspberry Pi
By 作者: Tim Cox – Dr. Steven Lawrence Fernandes – Sai Yamanoor – Srihari Yamanoor – Prof. Diwakar Vaish
ISBN-10 书号: 183855579X
ISBN-13 书号: 9781838555795
Release Finelybook 出版日期: 2019-02-26
pages 页数: (732 )

$49.99

Book Description to Finelybook sorting
Build clever, collaborative, and powerful automation systems with the Raspberry Pi and Python.
This Learning Path takes you on a journey in the world of robotics and teaches you all that you can achieve with Raspberry Pi and Python.
It teaches you to harness the power of Python with the Raspberry Pi 3 and the Raspberry Pi zero to build superlative automation systems that can transform your business. You will learn to create text classifiers, predict sentiment in words, and develop applications with the Tkinter library. Things will get more interesting when you build a human face detection and recognition system and a home automation system in Python, where different appliances are controlled using the Raspberry Pi. With such diverse robotics projects, you’ll grasp the basics of robotics and its functions, and understand the integration of robotics with the IoT environment.
By the end of this Learning Path, you will have covered everything from configuring a robotic controller, to creating a self-driven robotic vehicle using Python.

Raspberry Pi 3 Cookbook for Python Programmers – Third Edition by Tim Cox, Dr. Steven Lawrence Fernandes
Python Programming with Raspberry Pi by Sai Yamanoor, Srihari Yamanoor
Python Robotics Projects by Prof. Diwakar Vaish
What you will learn

Build text classifiers and predict sentiment in words with the Tkinter library
Develop human face detection and recognition systems
Create a neural network module for optical character recognition
Build a mobile robot using the Raspberry Pi as a controller
Understand how to interface sensors, actuators, and LED displays work
Apply machine learning techniques to your models
Interface your robots with Bluetooth

contents
1 Getting Started with a Raspberry Pi 3 Computer
2 Dividing Text Data and Building Text Classifiers
3 Using Python for Automation and Productivity
4 Predicting Sentiments in Words
5 Detecting Edges and Contours in Images
6 Building Face Detector and Face Recognition Applications
7 Using Python to Drive Hardware
8 Sensing and Displaying Real-World Data
9 Building Neural Network Modules for Optical Character Recognition
10 Arithmetic Operations, Loops, and Blinky Lights
11 Conditional Statements, Functions, and Lists
12 Communication Interfaces
13 Data Types and Object-Oriented Programming in Python
14 File I/O and Python Utilities
15 Requests and Web Frameworks
16 Awesome Things You Could Develop Using Python
17 Robotics 101
18 Using GPIOs as Input
19 Making a Gardener Robot
20 Basics of Motors
21 Bluetooth-Controlled Robotic Car
22 Sensor Interface for Obstacle Avoidance
23 Making Your Own Area Scanner
24 Basic Switching
25 Recognizing Humans with Jarvis
26 Making Jarvis IoT Enabled
27 Giving Voice to Jarvis
28 Gesture Recognition
29 Machine Learning
30 Making a Robotic Arm