Mastering TensorFlow 1.x. Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

Armando Fandango

TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs.This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim, Pretty Tensor, and Sonnet. Leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Throughout the book, you will obtain hands-on experience with varied datasets, such as MNIST, CIFAR-10, PTB, text8, and COCO-Images.You will learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF Clusters, deploy production models with TensorFlow Serving, and build and deploy TensorFlow models for mobile and embedded devices on Android and iOS platforms. You will see how to call TensorFlow and Keras API within the R statistical software, and learn the required techniques for debugging when the TensorFlow API-based code does not work as expected.The book helps you obtain in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems. By the end of this guide, you will have mastered the offerings of TensorFlow and Keras, and gained the skills you need to build smarter, faster, and efficient machine learning and deep learning systems.

Kubernetes on AWS. Deploy and manage production-ready Kubernetes clusters on AWS

Ed Robinson

Docker containers promise to radicalize the way developers and operations build, deploy, and manage applications running on the cloud. Kubernetes provides the orchestration tools you need to realize that promise in production.Kubernetes on AWS guides you in deploying a production-ready Kubernetes cluster on the AWS platform. You will then discover how to utilize the power of Kubernetes, which is one of the fastest growing platforms for production-based container orchestration, to manage and update your applications. Kubernetes is becoming the go-to choice for production-grade deployments of cloud-native applications. This book covers Kubernetes from first principles. You will start by learning about Kubernetes' powerful abstractions - Pods and Services - that make managing container deployments easy. This will be followed by a guided tour through setting up a production-ready Kubernetes cluster on AWS, while learning the techniques you need to successfully deploy and manage your own applications.By the end of the book, you will have gained plenty of hands-on experience with Kubernetes on Amazon Web Services. You will also have picked up some tips on deploying and managing applications, keeping your cluster and applications secure, and ensuring that your whole system is reliable and resilient to failure.

Python Machine Learning Blueprints. Put your machine learning concepts to the test by developing real-world smart projects - Second Edition

Alexander Combs, Michael Roman

Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects.The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks.By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects.

Machine Learning with Apache Spark Quick Start Guide. Uncover patterns, derive actionable insights, and learn from big data using MLlib

Jillur Quddus

Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently.But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it?The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data.

Learning Microsoft Azure Storage. Build large-scale, real-world apps by effectively planning, deploying, and implementing Azure storage solutions

Mohamed Waly

Microsoft Azure Storage is the bedrock of Microsoft's core storage solution offering in Azure. No matter what solution you are building for the cloud, you'll find a compelling use for Azure Storage. This book will help you get up-to-speed quickly on Microsoft Azure Storage by teaching you how to use the different storage services. You will be able to leverage secure design patterns based on real-world scenarios and develop a strong storage foundation for Azure virtual machines.You will start this book with an introduction to Microsoft Azure storage and how it can be used to build large-scale, real-world applications using Azure storage services such as blob, table, queue, and file. This book will also teach you about the different types of Azure Storage. You will then find out the best practices for designing your Azure VM storage, whether it is Windows based or Linux based and how to migrate your storage in different scenarios. You will learn also how to plan and implement your SQL database solution on Azure, and how to build your SQL database in different service models (IaaS/PaaS). Moreover, you will also learn best practices for dealing with Azure Backup, the role of Azure Site Recovery, and the solutions they offer in different scenarios. Finally, you will use StorSimple to unlock the maximum value from all of your data, and some tools that will help you manage your storage on-and off-premise (Azure), such as AzCopy and Storage Explorer. Monitoring your storage in no laughing matter, so you will learn to monitor, diagnose and troubleshoot it.

Java 9 Data Structures and Algorithms. A step-by-step guide to data structures and algorithms

Debasish Ray Chawdhuri

Java 9 Data Structures and Algorithms covers classical, functional, and reactive data structures, giving you the ability to understand computational complexity, solve problems, and write efficient code. This book is based on the Zero Bug Bounce milestone of Java 9.We start off with the basics of algorithms and data structures, helping you understand the fundamentals and measure complexity. From here, we introduce you to concepts such as arrays, linked lists, as well as abstract data types such as stacks and queues. Next, we’ll take you through the basics of functional programming while making sure you get used to thinking recursively.We provide plenty of examples along the way to help you understand each concept. You will also get a clear picture of reactive programming, binary searches, sorting, search trees, undirected graphs, and a whole lot more!

Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA. Effective techniques for processing complex image data in real time using GPUs

Bhaumik Vaidya

Computer vision has been revolutionizing a wide range of industries, and OpenCV is the most widely chosen tool for computer vision with its ability to work in multiple programming languages. Nowadays, in computer vision, there is a need to process large images in real time, which is difficult to handle for OpenCV on its own. This is where CUDA comes into the picture, allowing OpenCV to leverage powerful NVDIA GPUs. This book provides a detailed overview of integrating OpenCV with CUDA for practical applications. To start with, you’ll understand GPU programming with CUDA, an essential aspect for computer vision developers who have never worked with GPUs. You’ll then move on to exploring OpenCV acceleration with GPUs and CUDA by walking through some practical examples.Once you have got to grips with the core concepts, you’ll familiarize yourself with deploying OpenCV applications on NVIDIA Jetson TX1, which is popular for computer vision and deep learning applications. The last chapters of the book explain PyCUDA, a Python library that leverages the power of CUDA and GPUs for accelerations and can be used by computer vision developers who use OpenCV with Python.By the end of this book, you’ll have enhanced computer vision applications with the help of this book's hands-on approach.

Mastering Elastic Stack. Dive into data analysis with a pursuit of mastering ELK Stack on real-world scenarios

Ravi Kumar Gupta, Yuvraj Gupta

Even structured data is useless if it can’t help you to take strategic decisions and improve existing system. If you love to play with data, or your job requires you to process custom log formats, design a scalable analysis system, and manage logs to do real-time data analysis, this book is your one-stop solution. By combining the massively popular Elasticsearch, Logstash, Beats, and Kibana, elastic.co has advanced the end-to-end stack that delivers actionable insights in real time from almost any type of structured or unstructured data source. If your job requires you to process custom log formats, design a scalable analysis system, explore a variety of data, and manage logs, this book is your one-stop solution. You will learn how to create real-time dashboards and how to manage the life cycle of logs in detail through real-life scenarios.This book brushes up your basic knowledge on implementing the Elastic Stack and then dives deeper into complex and advanced implementations of the Elastic Stack. We’ll help you to solve data analytics challenges using the Elastic Stack and provide practical steps on centralized logging and real-time analytics with the Elastic Stack in production. You will get to grip with advanced techniques for log analysis and visualization. Newly announced features such as Beats and X-Pack are also covered in detail with examples.Toward the end, you will see how to use the Elastic stack for real-world case studies and we’ll show you some best practices and troubleshooting techniques for the Elastic Stack.

Hands-On Geospatial Analysis with R and QGIS. A beginner’s guide to manipulating, managing, and analyzing spatial data using R and QGIS 3.2.2

Shammunul Islam

Managing spatial data has always been challenging and it's getting more complex as the size of data increases. Spatial data is actually big data and you need different tools and techniques to work your way around to model and create different workflows. R and QGIS have powerful features that can make this job easier.This book is your companion for applying machine learning algorithms on GIS and remote sensing data. You’ll start by gaining an understanding of the nature of spatial data and installing R and QGIS. Then, you’ll learn how to use different R packages to import, export, and visualize data, before doing the same in QGIS. Screenshots are included to ease your understanding.Moving on, you’ll learn about different aspects of managing and analyzing spatial data, before diving into advanced topics. You’ll create powerful data visualizations using ggplot2, ggmap, raster, and other packages of R. You’ll learn how to use QGIS 3.2.2 to visualize and manage (create, edit, and format) spatial data. Different types of spatial analysis are also covered using R. Finally, you’ll work with landslide data from Bangladesh to create a landslide susceptibility map using different machine learning algorithms.By reading this book, you’ll transition from being a beginner to an intermediate user of GIS and remote sensing data in no time.

Blender for Video Production Quick Start Guide. Create high quality videos for YouTube and other social media platforms with Blender

Allan Brito

One of the critical components of any workflow related to video production is a reliable tool to create and edit media such as video and audio. In most cases, you will find video producers using software that can only cut and mount video in a traditional way. What if you could use a software that offers not only options to edit and cut video, but also create 3D content and animation? With Blender, you can make use of a fantastic set of tools to edit and cut video, and also produce 3D content that will enable you to take your productions to the next level.Do you want to take footage from a camera and cut or add sound and titles? This book will show you how Blender can do that for you! You will learn to add 3D virtual objects to the same footage that will help you to create a full 3D environment. Using some camera tricks, you can even turn Blender into a powerful 2.5D animation software to create compelling infographics to produce educational, marketing, and instructional videos. You will also learn how to work with motion tracking to mix live-action footage with virtual objects. You will then learn how to use the video editing capabilities of Blender and match 3D content to your project for YouTube or any other media.Toward the end of the book, you will export the project to YouTube using optimal settings for the best performance in the platform.

Redash v5 Quick Start Guide. Create and share interactive dashboards using Redash

Alexander Leibzon, Yael Leibzon

Data exploration and visualization is vital to Business Intelligence, the backbone of almost every enterprise or organization. Redash is a querying and visualization tool developed to simplify how marketing and business development departments are exposed to data. If you want to learn to create interactive dashboards with Redash, explore different visualizations, and share the insights with your peers, then this is the ideal book for you.The book starts with essential Business Intelligence concepts that are at the heart of data visualizations. You will learn how to find your way round Redash and its rich array of data visualization options for building interactive dashboards. You will learn how to create data storytelling and share these with peers. You will see how to connect to different data sources to process complex data, and then visualize this data to reveal valuable insights. By the end of this book, you will be confident with the Redash dashboarding tool to provide insight and communicate data storytelling.

Kali Linux Cookbook. Effective penetration testing solutions - Second Edition

Corey P. Schultz, Bob Perciaccante

Kali Linux is a Linux distribution designed for penetration testing and security auditing. It is the successor to BackTrack, the world’s most popular penetration testing distribution. Kali Linux is the most widely used platform and toolkit for penetration testing. Security is currently the hottest field in technology with a projected need for millions of security professionals. This book focuses on enhancing your knowledge in Kali Linux for security by expanding your skills with toolkits and frameworks that can increase your value as a security professional.Kali Linux Cookbook, Second Edition starts by helping you install Kali Linux on different options available. You will also be able to understand the lab architecture and install a Windows host for use in the lab. Next, you will understand the concept of vulnerability analysis and look at the different types of exploits. The book will introduce you to the concept and psychology of Social Engineering and password cracking. You will then be able to use these skills to expand the scope of any breaches you create. Finally, the book will guide you in exploiting specific technologies and gaining access to other systems in the environment. By the end of this book, you will have gained the core knowledge and concepts of the penetration testing process.

Practical Computer Vision. Extract insightful information from images using TensorFlow, Keras, and OpenCV

Abhinav Dadhich

In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects.With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow. You'll get started with semantic segmentation using FCN models and track objects with Deep SORT. Not only this, you will also use Visual SLAM techniques such as ORB-SLAM on a standard dataset. By the end of this book, you will have a firm understanding of the different computer vision techniques and how to apply them in your applications.

R Data Analysis Cookbook. Customizable R Recipes for data mining, data visualization and time series analysis - Second Edition

Kuntal Ganguly, Shanthi Viswanathan, Viswa Viswanathan

Data analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data.This book will show you how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks. Right from acquiring your data and preparing it for analysis to the more complex data analysis techniques, the book will show you how you can implement each technique in the best possible manner. You will also visualize your data using the popular R packages like ggplot2 and gain hidden insights from it. Starting with implementing the basic data analysis concepts like handling your data to creating basic plots, you will master the more advanced data analysis techniques like performing cluster analysis, and generating effective analysis reports and visualizations. Throughout the book, you will get to know the common problems and obstacles you might encounter while implementing each of the data analysis techniques in R, with ways to overcoming them in the easiest possible way.By the end of this book, you will have all the knowledge you need to become an expert in data analysis with R, and put your skills to test in real-world scenarios.

Big Data Analytics with Hadoop 3. Build highly effective analytics solutions to gain valuable insight into your big data

Sridhar Alla

Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples.Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases.By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly.

Python Web Scraping. Hands-on data scraping and crawling using PyQT, Selnium, HTML and Python - Second Edition

Katharine Jarmul

The Internet contains the most useful set of data ever assembled, most of which is publicly accessible for free. However, this data is not easily usable. It is embedded within the structure and style of websites and needs to be carefully extracted. Web scraping is becoming increasingly useful as a means to gather and make sense of the wealth of information available online.This book is the ultimate guide to using the latest features of Python 3.x to scrape data from websites. In the early chapters, you'll see how to extract data from static web pages. You'll learn to use caching with databases and files to save time and manage the load on servers. Aftercovering the basics, you'll get hands-on practice building a more sophisticated crawler using browsers, crawlers, and concurrent scrapers.You'll determine when and how to scrape data from a JavaScript-dependent website using PyQt and Selenium. You'll get a better understanding of how to submit forms on complex websites protected by CAPTCHA. You'll find out how to automate these actions with Python packages such as mechanize. You'll also learn how to create class-based scrapers with Scrapy libraries and implement your learning on real websites.By the end of the book, you will have explored testing websites with scrapers, remote scraping, best practices, working with images, and many other relevant topics.