TinyML Cookbook. Combine artificial intelligence and ultra-low-power embedded devices to make the world smarter

Gian Marco Iodice, Ronan Naughton

This book explores TinyML, a fast-growing field at the unique intersection of machine learning and embedded systems to make AI ubiquitous with extremely low-powered devices such as microcontrollers.The TinyML Cookbook starts with a practical introduction to this multidisciplinary field to get you up to speed with some of the fundamentals for deploying intelligent applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico. As you progress, you’ll tackle various problems that you may encounter while prototyping microcontrollers, such as controlling the LED state with GPIO and a push-button, supplying power to microcontrollers with batteries, and more. Next, you’ll cover recipes relating to temperature, humidity, and the three “V” sensors (Voice, Vision, and Vibration) to gain the necessary skills to implement end-to-end smart applications in different scenarios. Later, you’ll learn best practices for building tiny models for memory-constrained microcontrollers. Finally, you’ll explore two of the most recent technologies, microTVM and microNPU that will help you step up your TinyML game.By the end of this book, you’ll be well-versed with best practices and machine learning frameworks to develop ML apps easily on microcontrollers and have a clear understanding of the key aspects to consider during the development phase.

Data Analysis Foundations with Python. Master Data Analysis with Python: From Basics to Advanced Techniques

Cuantum Technologies LLC

Embark on a comprehensive journey through data analysis with Python. Begin with an introduction to data analysis and Python, setting a strong foundation before delving into Python programming basics. Learn to set up your data analysis environment, ensuring you have the necessary tools and libraries at your fingertips. As you progress, gain proficiency in NumPy for numerical operations and Pandas for data manipulation, mastering the skills to handle and transform data efficiently.Proceed to data visualization with Matplotlib and Seaborn, where you'll create insightful visualizations to uncover patterns and trends. Understand the core principles of exploratory data analysis (EDA) and data preprocessing, preparing your data for robust analysis. Explore probability theory and hypothesis testing to make data-driven conclusions and get introduced to the fundamentals of machine learning. Delve into supervised and unsupervised learning techniques, laying the groundwork for predictive modeling.To solidify your knowledge, engage with two practical case studies: sales data analysis and social media sentiment analysis. These real-world applications will demonstrate best practices and provide valuable tips for your data analysis projects.

Flask Blueprints. Dive into the world of the Flask microframework to develop an array of web applications

Joel Perras

Data Acquisition using LabVIEW. Click here to enter text

Behzad Ehsani

NI LabVIEW's intuitive graphical interface eliminates the steep learning curve associated with text-based languages such as C or C++. LabVIEW is a proven and powerful integrated development environment to interact with measurement and control hardware, analyze data, publish results, and distribute systems. This hands-on tutorial guide helps you harness the power of LabVIEW for data acquisition. This book begins with a quick introduction to LabVIEW, running through the fundamentals of communication and data collection. Then get to grips with the auto-code generation feature of LabVIEW using its GUI interface. You will learn how to use NI-DAQmax Data acquisition VIs, showing how LabVIEW can be used to appropriate a true physical phenomenon (such as temperature, light, and so on) and convert it to an appropriate data type that can be manipulated and analyzed with a computer. You will also learn how to create Distribution Kit for LabVIEW, acquainting yourself with various debugging techniques offered by LabVIEW to help you in situations where bugs are not letting you run your programs as intended.By the end of the book, you will have a clear idea how to build your own data acquisition system independently and much more.

Learning PostgreSQL. Create, develop and manage relational databases in real world applications using PostgreSQL

Salahaldin Juba, Andrey Volkov, Salahaldin Juba, Achim Vannahme

PostgreSQL is one of the most powerful and easy to use database management systems. It supports the most advanced features included in SQL standards. The book starts with the introduction of relational databases with PostegreSQL. It then moves on to covering data definition language (DDL) with emphasis on PostgreSQL and common DDL commands supported by ANSI SQL. You will then learn the data manipulation language (DML), and advanced topics like locking and multi version concurrency control (MVCC). This will give you a very robust background to tune and troubleshoot your application. The book then covers the implementation of data models in the database such as creating tables, setting up integrity constraints, building indexes, defining views and other schema objects. Next, it will give you an overview about the NoSQL capabilities of PostgreSQL along with Hstore, XML, Json and arrays. Finally by the end of the book, you'll learn to use the JDBC driver and manipulate data objects in the Hibernate framework.

Learning Docker. Optimize the power of Docker to run your applications quickly and easily

Pethuru Raj, Jeeva S. Chelladhurai, Vinod Singh, Vinod kumar Singh, ...

AWS Certified Cloud Practitioner Exam Guide. Build your cloud computing knowledge and build your skills as an AWS Certified Cloud Practitioner (CLF-C01)

Rajesh Daswani

Amazon Web Services is the largest cloud computing service provider in the world. Its foundational certification, AWS Certified Cloud Practitioner (CLF-C01), is the first step to fast-tracking your career in cloud computing. This certification will add value even to those in non-IT roles, including professionals from sales, legal, and finance who may be working with cloud computing or AWS projects. If you are a seasoned IT professional, this certification will make it easier for you to prepare for more technical certifications to progress up the AWS ladder and improve your career prospects.The book is divided into four parts. The first part focuses on the fundamentals of cloud computing and the AWS global infrastructure. The second part examines key AWS technology services, including compute, network, storage, and database services. The third part covers AWS security, the shared responsibility model, and several security tools. In the final part, you'll study the fundamentals of cloud economics and AWS pricing models and billing practices.Complete with exercises that highlight best practices for designing solutions, detailed use cases for each of the AWS services, quizzes, and two complete practice tests, this CLF-C01 exam study guide will help you gain the knowledge and hands-on experience necessary to ace the AWS Certified Cloud Practitioner exam.

Migrating Linux to Microsoft Azure. A hands-on guide to efficiently relocating your Linux workload to Azure

Rithin Skaria, Toni Willberg

With cloud adoption at the core of digital transformation for organizations, there has been a significant demand for deploying and hosting enterprise business workloads in the cloud. Migrating Linux to Microsoft Azure offers a wealth of actionable insights into deploying Linux workload to Azure.You'll begin by learning about the history of IT, operating systems, Unix, Linux, and Windows before moving on to look at the cloud and what things were like before virtualization. This will help anyone new to Linux become familiar with the terms used throughout the book. You'll then explore popular Linux distributions, including RHEL 7, RHEL 8, SLES, Ubuntu Pro, CentOS 7, and more.As you progress, you'll cover the technical details of Linux workloads such as LAMP, Java, and SAP, and understand how to assess your current environment and prepare for your migration to Azure through cloud governance and operations planning. Finally, you'll go through the execution of a real-world migration project and learn how to analyze and debug some common problems that Linux on Azure users may encounter.By the end of this Linux book, you'll be proficient at performing an effective migration of Linux workloads to Azure for your organization.