The DIY trend for women involves more than knitting and sewing: today more women are tending to their homes, and they're not just sewing curtains and arranging flowers. They're installing new toilets, laying ceramic floors in the kitchen, and drywalling the den. With 23 percent of all power tool purchases in 2004 made by women, and the number of unmarried females owning homes climbing by nearly 4 million owners from 1994 to 2002, when it comes to home repair, maintenance, and improvement, these sisters are doing it for themselves.

Woodworker’s Journal предназначен для всех столяров (от любителей до профессионалов), которые ищут новые идеи проектов, методы деревообработки и советы. Проекты представляются в детальном пошаговом формате с фотографиями и иллюстрациями. В середине каждого выпуска вставляется полноразмерный шаблон. Отделы охватывают столярные изделия, отделочные работы, изделия, технику и оборудование.

Today more women are tending to their homes, and they're not just sewing curtains and arranging flowers. They're installing new toilets, adding ceramic floors to the kitchen, and drywalling the den. A survey by Home Depot found that 73 percent of women would like to learn more about tackling home improvements. But who has the brains, brawn, and beauty to really understand a woman's perspective and give her the confidence to conquer what had traditionally been men's territory? Norma Vally.

Каждая хозяйка сталкивалась с ситуацией, когда требуется накрыть на стол в считанные минуты. Возможно ли приготовить вкусные и оригинальные блюда на скорую руку? Конечно! Нужно только знать подходящий рецепт. В этой книге мы собрали самые «быстрые» и вкусные рецепты салатов, закусок, первых и вторых блюд, которые стоит взять на заметку каждой хозяйке. Эта книжка - настоящий подарок для хозяйки. В ней собраны самые необходимые рецепты блюд на скорую руку.

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.