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.

Данное учебное пособие ориентировано на формирование у студентов навыков и знаний в теории моделирования систем и сетей с целью последующего их анализа и оптимизации с использованием современных компьютерных технологий. В конце глав приведены вопросы, которые позволят на практике освоить теоретический материал. В пособии кратко изложены основы теории моделирования систем, приведены различные виды классификации моделирования и моделей, рассмотрена математическая основа моделирования сетей, средства моделирования сетей, а также разработан практический курс в рамках дисциплины «моделирование сетей ЭВМ и систем телекоммуникаций».

Windows IT Pro/RE – профессиональное издание на русском языке, целиком и полностью посвященное вопросам работы с продуктами семейства Windows и технологиям компании Microsoft. Каждый номер журнала начинается со статей, посвященных одной из самых перспективных на данный момент технологий, оказывающих серьезное влияние на ИТ-отрасль и вызывающих интерес сообщества профессионалов Windows.
Целевая аудитория: системные администраторы, администраторы баз данных, разработчики, технические руководители, специалисты по безопасности, пользователи, работающие с ОС Windows и офисными продуктами компании Microsoft.
Основан в 1999 году. Издается по лицензии Penton Media, Inc.

В отличие от основной массы литературы про Lisp, эта книга не просто рассказывает о ряде возможностей языка, предоставляя читателю самостоятельно осваивать их на практике. Здесь будут описаны все функции языка, которые понадобятся вам для написания реальных программ. Более трети книги посвящено разработке нетривиальных программ - статистического фильтра для спама, библиотеки для разбора двоичных файлов и сервера для трансляции музыки в формате MP3 через сеть, включающего в себя базу данных (MP3-файлов) и веб-интерфейс. Издание прнедназначено для программистов различной квалификации, как уже использующих Lisp в своей работе, так и только знакомящихся с этим языком.

Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value.

Network forensics is a subset of digital forensics that deals with network attacks and their investigation. In the era of network attacks and malware threat, it’s now more important than ever to have skills to investigate network attacks and vulnerabilities. Hands-On Network Forensics starts with the core concepts within network forensics, including coding, networking, forensics tools, and methodologies for forensic investigations. You’ll then explore the tools used for network forensics, followed by understanding how to apply those tools to a PCAP file and write the accompanying report. In addition to this, you will understand how statistical flow analysis, network enumeration, tunneling and encryption, and malware detection can be used to investigate your network. Towards the end of this book, you will discover how network correlation works and how to bring all the information from different types of network devices together. By the end of this book, you will have gained hands-on experience of performing forensics analysis tasks.

IBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio.

Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this book, you'll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems. The book begins with an introduction to data manipulation in Python using pandas. You'll then get familiar with statistical analysis and plotting techniques. With multiple hands-on activities in store, you'll be able to analyze data that is distributed on several computers by using Dask.

Blockchain and Hyperledger are open source technologies that power the development of decentralized applications. This Learning Path is your helpful reference for exploring and building blockchain networks using Ethereum, Hyperledger Fabric, and Hyperledger Composer. Blockchain Development with Hyperledger will start off by giving you an overview of blockchain and demonstrating how you can set up an Ethereum development environment for developing, packaging, building, and testing campaign-decentralized applications. You'll then explore the de facto language Solidity, which you can use to develop decentralized applications in Ethereum.

GCP is a cloud computing platform with a wide range of products and services that enable you to build and deploy cloud-hosted applications. This Learning Path will guide you in using GCP and designing, deploying, and managing applications on Google Cloud. You will get started by learning how to use App Engine to access Google's scalable hosting and build software that runs on this framework. With the help of Google Compute Engine, you’ll be able to host your workload on virtual machine instances. The later chapters will help you to explore ways to implement authentication and security, Cloud APIs, and command-line and deployment management. As you hone your skills, you’ll understand how to integrate your new applications with various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage.