Microsoft Power BI Cookbook. Creating Business Intelligence Solutions of Analytical Data Models, Reports, and Dashboards

Brett Powell, Gilbert Quevauvilliers

Microsoft Power BI is a business intelligence and analytics platform consisting of applications and services designed to provide coherent, visual and interactive insights of data.This book will provide thorough, technical examples of using all primary Power BI tools and features as well as demonstrate high impact end-to-end solutions that leverage and integrate these technologies and services. Get familiar with Power BI development tools and services, go deep into the data connectivity and transformation, modeling, visualization and analytical capabilities of Power BI, and see Power BI’s functional programming languages of DAX and M come alive to deliver powerful solutions to address common, challenging scenarios in business intelligence.This book will excite and empower you to get more out of Power BI via detailed recipes, advanced design and development tips, and guidance on enhancing existing Power BI projects.

Python Network Programming. Conquer all your networking challenges with the powerful Python language

Abhishek Ratan, Eric Chou, Pradeeban Kathiravelu, Dr. M. O. Faruque Sarker

This Learning Path highlights major aspects of Python network programming such as writing simple networking clients, creating and deploying SDN and NFV systems, and extending your network with Mininet. You’ll also learn how to automate legacy and the latest network devices. As you progress through the chapters, you’ll use Python for DevOps and open source tools to test, secure, and analyze your network. Toward the end, you'll develop client-side applications, such as web API clients, email clients, SSH, and FTP, using socket programming.By the end of this Learning Path, you will have learned how to analyze a network's security vulnerabilities using advanced network packet capture and analysis techniques. This Learning Path includes content from the following Packt products:• Practical Network Automation by Abhishek Ratan • Mastering Python Networking by Eric Chou • Python Network Programming Cookbook, Second Edition by Pradeeban Kathiravelu, Dr. M. O. Faruque Sarker

Tkinter GUI Programming by Example. Learn to create modern GUIs using Tkinter by building real-world projects in Python

David Love

Tkinter is a modular, cross-platform application development toolkit for Python. When developing GUI-rich applications, the most important choices are which programming language(s) and which GUI framework to use. Python and Tkinter prove to be a great combination. This book will get you familiar with Tkinter by having you create fun and interactive projects. These projects have varying degrees of complexity. We'll start with a simple project, where you'll learn the fundamentals of GUI programming and the basics of working with a Tkinter application. After getting the basics right, we'll move on to creating a project of slightly increased complexity, such as a highly customizable Python editor. In the next project, we'll crank up the complexity level to create an instant messaging app. Toward the end, we'll discuss various ways of packaging our applications so that they can be shared and installed on other machines without the user having to learn how to install and run Python programs.

Metasploit Bootcamp. The fastest way to learn Metasploit

Nipun Jaswal

The book starts with a hands-on Day 1 chapter, covering the basics of the Metasploit framework and preparing the readers for a self-completion exercise at the end of every chapter. The Day 2 chapter dives deep into the use of scanning and fingerprinting services with Metasploit while helping the readers to modify existing modules accordingto their needs. Following on from the previous chapter, Day 3 will focus on exploiting various types of service and client-side exploitation while Day 4 will focus on post-exploitation, and writing quick scripts that helps with gathering the required information from the exploited systems. The Day 5 chapter presents the reader with the techniquesinvolved in scanning and exploiting various services, such as databases, mobile devices, and VOIP. The Day 6 chapter prepares the reader to speed up and integrate Metasploit with leading industry tools for penetration testing. Finally, Day 7 brings in sophisticated attack vectors and challenges based on the user’s preparation over the past six days and ends with a Metasploit challenge to solve.

scikit-learn Cookbook. Over 80 recipes for machine learning in Python with scikit-learn - Second Edition

Julian Avila, Trent Hauck

Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility, and within the Python data space, scikit-learn is the unequivocal choice for machine learning. This book includes walk throughs and solutions to the common as well as the not-so-common problems in machine learning, and how scikit-learn can be leveraged to perform various machine learning tasks effectively.The second edition begins with taking you through recipes on evaluating the statistical properties of data and generates synthetic data for machine learning modelling. As you progress through the chapters, you will comes across recipes that will teach you to implement techniques like data pre-processing, linear regression, logistic regression, K-NN, Naïve Bayes, classification, decision trees, Ensembles and much more. Furthermore, you’ll learn to optimize your models with multi-class classification, cross validation, model evaluation and dive deeper in to implementing deep learning with scikit-learn. Along with covering the enhanced features on model section, API and new features like classifiers, regressors and estimators the book also contains recipes on evaluating and fine-tuning the performance of your model. By the end of this book, you will have explored plethora of features offered by scikit-learn for Python to solve any machine learning problem you come across.

ArcPy and ArcGIS. Automating ArcGIS for Desktop and ArcGIS Online with Python - Second Edition

Silas Toms, Dara OBeirne

ArcGIS allows for complex analyses of geographic information. The ArcPy module is used to script these ArcGIS analyses, providing a productive way to perform geo-analyses and automate map production.The second edition of the book focuses on new Python tools, such as the ArcGIS API for Python. Using Python, this book will guide you from basic Python scripting to advanced ArcPy script tools.This book starts off with setting up your Python environment for ArcGIS automation. Then you will learn how to output maps using ArcPy in MXD and update feature class in a geodatabase using arcpy and ArcGIS Online. Next, you will be introduced to ArcREST library followed by examples on querying, updating and manipulating ArcGIS Online feature services. Further, you will be enabling your scripts in the browser and directly interacting with ArcGIS Online using Jupyter notebook. Finally, you can learn ways to use of ArcPy to control ArcGIS Enterprise and explore topics on deployments, data quality assurances, data updates, version control, and editing safeguards.By the end of the book, you will be equipped with the knowledge required to create automated analysis with administration reducing the time-consuming nature of GIS.

Hands-On Transfer Learning with Python. Implement advanced deep learning and neural network models using TensorFlow and Keras

Dipanjan Sarkar, Raghav Bali, Tamoghna Ghosh

Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems. The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples. The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with practical examples. In the concluding chapters, we will focus on a multitude of real-world case studies and problems associated with areas such as computer vision, audio analysis and natural language processing (NLP).By the end of this book, you will be able to implement both DL and transfer learning principles in your own systems.

C++17 STL Cookbook. Discover the latest enhancements to functional programming and lambda expressions

Jacek Galowicz

C++ has come a long way and is in use in every area of the industry. Fast, efficient, and flexible, it is used to solve many problems. The upcoming version of C++ will see programmers change the way they code. If you want to grasp the practical usefulness of the C++17 STL in order to write smarter, fully portable code, then this book is for you.Beginning with new language features, this book will help you understand the language’s mechanics and library features, and offers insight into how they work. Unlike other books, ours takes an implementation-specific, problem-solution approach that will help you quickly overcome hurdles. You will learn the core STL concepts, such as containers, algorithms, utility classes, lambda expressions, iterators, and more, while working on practical real-world recipes. These recipes will help you get the most from the STL and show you how to program in a better way. By the end of the book, you will be up to date with the latest C++17 features and save time and effort while solving tasks elegantly using the STL.