Deep Learning with Theano. Perform large-scale numerical and scientific computations efficiently

Christopher Bourez

This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning models easy on CPU or GPU.The book provides some practical code examples that help the beginner understand how easy it is to build complex neural networks, while more experimented data scientists will appreciate the reach of the book, addressing supervised and unsupervised learning, generative models, reinforcement learning in the fields of image recognition, natural language processing, or game strategy.The book also discusses image recognition tasks that range from simple digit recognition, image classification, object localization, image segmentation, to image captioning. Natural language processing examples include text generation, chatbots, machine translation, and question answering. The last example deals with generating random data that looks real and solving games such as in the Open-AI gym. At the end, this book sums up the best -performing nets for each task. While early research results were based on deep stacks of neural layers, in particular, convolutional layers, the book presents the principles that improved the efficiency of these architectures, in order to help the reader build new custom nets.

Bootstrap 4 Cookbook. Solutions to common problems faced in Responsive Web Design

Ajdin Imsirovic

Bootstrap, one of the most popular front-end frameworks, is perfectly built to design elegant, powerful, and responsive interfaces for professional-level web pages. It supports responsive design by dynamically adjusting your web page layout.Bootstrap 4 is a major update with many impressive changes that greatly enhance the end results produced by Bootstrap. This cookbook is a collection of great recipes that show you how to use all the latest features of Bootstrap to build compelling UIs.This book is using the most up-to-date version of Bootstrap 4 in all its chapters. First off, you will be shown how you can leverage the latest core features of Bootstrap 4 to create stunning web pages and responsive media. You will gradually move on to extending Bootstrap 4 with the help of plugins to build highly customized and powerful UIs.By the end of this book, you will know how to leverage, extend, and integrate bootstrap to achieve optimal results for your web projects.

Learning Android Forensics. Analyze Android devices with the latest forensic tools and techniques - Second Edition

Oleg Skulkin, Donnie Tindall, Rohit Tamma

Many forensic examiners rely on commercial, push-button tools to retrieve and analyze data, even though there is no tool that does either of these jobs perfectly.Learning Android Forensics will introduce you to the most up-to-date Android platform and its architecture, and provide a high-level overview of what Android forensics entails. You will understand how data is stored on Android devices and how to set up a digital forensic examination environment. As you make your way through the chapters, you will work through various physical and logical techniques to extract data from devices in order to obtain forensic evidence. You will also learn how to recover deleted data and forensically analyze application data with the help of various open source and commercial tools. In the concluding chapters, you will explore malware analysis so that you’ll be able to investigate cybersecurity incidents involving Android malware.By the end of this book, you will have a complete understanding of the Android forensic process, you will have explored open source and commercial forensic tools, and will have basic skills of Android malware identification and analysis.

Practical Machine Learning Cookbook. Supervised and unsupervised machine learning simplified

Atul Tripathi

Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge. This cookbook will help solve everyday challenges you face as a data scientist. The application of various data science techniques and on multiple data sets based on real-world challenges you face will help you appreciate a variety of techniques used in various situations.The first half of the book provides recipes on fairly complex machine-learning systems, where you’ll learn to explore new areas of applications of machine learning and improve its efficiency. That includes recipes on classifications, neural networks, unsupervised and supervised learning, deep learning, reinforcement learning, and more.The second half of the book focuses on three different machine learning case studies, all based on real-world data, and offers solutions and solves specific machine-learning issues in each one.

Practical Internet of Things with JavaScript. Build standalone exciting IoT projects with Raspberry Pi 3 and JavaScript (ES5/ES6)

Arvind Ravulavaru

In this world of technology upgrades, IoT is currently leading with its promise to make the world a more smarter and efficient place.This book will show you how to build simple IoT solutions that will help you to understand how this technology works. We would not only explore the IoT solution stack, but we will also see how to do it with the world’s most misunderstood programming language - JavaScript. Using Raspberry Pi 3 and JavaScript (ES5/ES6) as the base to build all the projects, you will begin with learning about the fundamentals of IoT and then build a standard framework for developing all the applications covered in this book. You will then move on to build a weather station with temperature, humidity and moisture sensors and further integrate Alexa with it. Further, you will build a smart wearable for understanding the concept of fall detection. You will then extend it with the 'If This Then That' (IFTTT) rules engine to send an email on fall detection. Finally, you will be working with the Raspberry Pi 3 camera module and surveillance with a bit of facial detection using Amazon Rekognition platform.At the end of the book, you will not only be able to build standalone exciting IoT applications but also learn how you can extend your projects to another level.

Data Analysis with Python. A Modern Approach

David Taieb

Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects.Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.

Java for Data Science. Examine the techniques and Java tools supporting the growing field of data science

Richard M. Reese, Jennifer L. Reese

para 1: Get the lowdown on Java and explore big data analytics with Java for Data Science. Packed with examples and data science principles, this book uncovers the techniques & Java tools supporting data science and machine learning. Para 2: The stability and power of Java combines with key data science concepts for effective exploration of data. By working with Java APIs and techniques, this data science book allows you to build applications and use analysis techniques centred on machine learning. Para 3: Java for Data Science gives you the understanding you need to examine the techniques and Java tools supporting big data analytics. These Java-based approaches allow you to tackle data mining and statistical analysis in detail. Deep learning and Java data mining are also featured, so you can explore and analyse data effectively, and build intelligent applications using machine learning. para 4: What?s Inside ? Understand data science principles with Java support ? Discover machine learning and deep learning essentials ? Explore data science problems with Java-based solutions

Jira Quick Start Guide. Manage your projects efficiently using the all-new Jira

Ravi Sagar

Jira is an issue tracker and project management system. With their latest release, the Jira team has now expanded their user base to agile teams as well as business teams. This book provides a comprehensive explanation covering all major components of Jira, including Jira Software, Jira Core, and Jira Service Desk.This book starts with an introduction to Jira's unique features and how it can be used as an issue-tracking tool. It will then teach you about how a new project is created by a Jira administrator, what responsibilities there are, and using correct and relevant schemes in your project. You will then learn how to configure project workflows and fields for project screens.You will understand the various permissions used in projects and the importance of project roles in Jira. Then, the book talks about the concepts of versions acting as milestones and using components when handling issues in your projects. It will then focus on analysing data using built-in reports and creating dashboards in Jira. At the end, it will discuss various best practices for users as well as project managers or project administrators.