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Architecting Microsoft Azure Solutions - Exam Guide 70-535
Architecting Microsoft Azure Solutions - Exam Guide 70-535

Architecting Microsoft Azure Solutions: Exam Guide 70-535 will get Azure architects and developers up-to-date with the latest updates on Azure from an architecture and design perspective. The book includes all the topics that are still relevant from the previous 70-534 exam, and is updated with latest topics covered, including Artificial Intelligence, IoT, and architecture styles. This exam guide is divided into six parts, where the first part will give you a good understanding of how to design a compute infrastructure. It also dives into designing networking and data implementations. You will learn about designing solutions for Platform Service and operations. Next, you will be able to secure your resources and data, as well as design a mechanism for governance and policies. You will also understand the objective of designing solutions for Platform Services, by covering Artificial Intelligence, IoT, media services, and messaging solution concepts. Finally, you will cover the design ...
Natural Language Processing and Computational Linguistics
Natural Language Processing and Computational Linguistics

Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for t ...
Microsoft Excel 2019 Inside Out
Microsoft Excel 2019 Inside Out

Dive into Microsoft Excel 2019 - and really put your spreadsheet expertise to work. This supremely organized reference packs hundreds of timesaving solutions, tips, and workarounds - all you need to make the most of Excel's most powerful tools for analyzing data and making better decisions. Renowned Excel expert Bill Jelen offers a complete tour of Excel 2019 and Excel in Office 365, from efficient interface customizations to advanced analysis, visualizations, and dashboards. Discover how experts tackle today's key tasks - and challenge yourself to new levels of mastery. Enter formulas more efficiently, and fully control operators and dates; Master the most widely-used functions in Excel; Integrate external data from the web and other sources; Easily transform complex datasets with Power Query; Quickly summarize millions of records with Pivot Tables; Perform ad hoc analyses with slicers and other filters; Create advanced data mashups with Power Pivot; Solve complex problems with Wha ...
Python Deep Learning Projects
Python Deep Learning Projects

Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system. Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects. By the end of ...
Learn Robotics Programming
Learn Robotics Programming

We live in an age where the most difficult human tasks are now automated. Smart and intelligent robots, which will perform different tasks precisely and efficiently, are the requirement of the hour. A combination of Raspberry Pi and Python works perfectly when making these kinds of robots. Learn Robotics Programming starts by introducing you to the basic structure of a robot, along with how to plan, build, and program it. As you make your way through the book, you will gradually progress to adding different outputs and sensors, learning new building skills, and writing code for interesting behaviors with sensors. You'll also be able to update your robot, and set up web, phone, and Wi-Fi connectivity in order to control it. By the end of the book, you will have built a clever robot that can perform basic artificial intelligence (AI) operations. ...
Grokking Deep Learning
Grokking Deep Learning

Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate ...
Building Digital Experience Platforms
Building Digital Experience Platforms

Use digital experience platforms (DXP) to improve your development productivity and release timelines. Leverage the pre-integrated feature sets of DXPs in your organization's digital transformation journey to quickly develop a personalized, secure, and robust enterprise platform. In this book the authors examine various features of DXPs and provide rich insights into building each layer in a digital platform. Proven best practices are presented with examples for designing and building layers. A special focus is provided on security and quality attributes needed for business-critical enterprise applications. The authors cover modern and emerging digital trends such as Blockchain, IoT, containers, chatbots, artificial intelligence, and more. The book is divided into five parts related to requirements/design, development, security, infrastructure, and case study. The authors employ proven real-world methods, best practices, and security and integration techniques derived from their ...
Python: Beginner's Guide to Artificial Intelligence
Python: Beginner's Guide to Artificial Intelligence

This Learning Path offers practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. You will be introduced to various machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. You'll find a new balance of classical ideas and modern insights into machine learning. You will learn to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open-source Python libraries. Throughout the Learning Path, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, and Autoencoders. Discover how to attain deep learning programming on GPU in a distributed way. By the end of this Learning Path, you know the fundamentals of AI and have worked through a n ...
Practical Network Automation, 2nd Edition
Practical Network Automation, 2nd Edition

Network automation is the use of IT controls to supervise and carry out everyday network management functions. It plays a key role in network virtualization technologies and network functions. The book starts by providing an introduction to network automation, and its applications, which include integrating DevOps tools to automate the network efficiently. It then guides you through different network automation tasks and covers various data digging and performing tasks such as ensuring golden state configurations using templates, interface parsing. This book also focuses on Intelligent Operations using Artificial Intelligence and troubleshooting using chatbots and voice commands. The book then moves on to the use of Python and the management of SSH keys for machine-to-machine (M2M) communication, all followed by practical use cases. The book also covers the importance of Ansible for network automation, including best practices in automation; ways to test automated networks using too ...
Introducing Machine Learning
Introducing Machine Learning

Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft's powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning. 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you; Explore what's known about how humans learn and how intelligent software is built; Discover which problems machine learning can address; Understand the machine learning pipeline: the steps lea ...
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