OpenCV with Python Blueprints. Design and develop advanced computer vision projects using OpenCV with Python

Michael Beyeler

Microsoft Exchange 2013 Cookbook. Get the most out of Microsoft Exchange with this comprehensive guide. Structured around a series of clear, step-by-step exercises it will help you deploy and configure both basic and advanced features for your enterprise

Michael Van Horenbeeck, Peter De Tender

OpenAI GPT For Python Developers. The art and science of building AI-powered apps with GPT-4, Whisper, Weaviate, and beyond

Aymen El Amri

“OpenAI GPT for Python Developers” is meticulously crafted to provide Python developers with a deep dive into the mechanics and applications of GPT technology, beginning with a captivating narrative on the evolution of OpenAI and the fundamental workings of GPT models. As readers progress, they will be expertly guided through the essential steps of setting up a development environment tailored for AI innovations, coupled with insightful advice on selecting the most appropriate GPT model to suit specific project needs.The guide progresses into practical tutorials that cover the implementation of chat completions and the art of prompt engineering, providing a solid foundation in harnessing the capabilities of GPT for generating human-like text responses. Practical applications are further expanded with discussions on the creation of autonomous AI-to-AI dialogues, the development of AI avatars, and the strategic use of AI in interactive applications.In addition to technical skills, this book addresses the ethical implications and prospects of AI technologies, encouraging a holistic view of AI development. The guide is enriched with detailed examples, step-by-step tutorials, and comprehensive explanations that illuminate the theoretical aspects and emphasize practical implementation.

Learning C# by Developing Games with Unity 3D Beginner's Guide. The beauty of this book is that it assumes absolutely no knowledge of coding at all. Starting from very first principles it will end up giving you an excellent grounding in the writing of C# code and scripts

Terry Norton

For the absolute beginner to any concept of programming, writing a script can appear to be an impossible hurdle to overcome. The truth is, there are only three simple concepts to understand: 1) having some type of information; 2) using the information; and 3) communicating the information. Each of these concepts is very simple and extremely important. These three concepts are combined to access the feature set provided by Unity.Learning C# by Developing Games with Unity 3D Beginner's Guide assumes that you know nothing about programming concepts. First you will learn the absolute basics of programming using everyday examples that you already know. As you progress through the book, you will find that C# is not a foreign language after all, because you already know the words. With a few keywords and using substitution, before you know it, you'll be thinking in code.The book starts by explaining in simple terms the three concepts you need for writing C# code and scripts: 1) variables to hold information; 2) methods (functions) to use the information; and 3) Dot Syntax to communicate the information where it's needed. The book builds on these concepts to open up the world of C# coding and Unity scripting. You will use this new power to access the features provided in Unity's Scripting Reference.The first half of this book is devoted to the code writing beginner. The concepts of variables, methods, Dot Syntax, and decision processing are fully explained. Since C# is an actual programming language, we take advantage of this to develop a State Machine to help control and organize each phase of a Unity project. Once the basic programming concepts are established and we have some State Machine organization, the features and power of Unity are accessed using the Scripting Reference.If you're looking to learn C# for Unity then this is the book that offers everything you need and more - so discover what C# offers today and see your work come to life as complete games!

Realistic Asset Creation with Adobe Substance 3D. Create materials, textures, filters, and 3D models using Substance 3D Painter, Designer, and Stager

Zeeshan Jawed Shah

Adobe Substance 3D is a comprehensive suite complete with everything an artist needs to create stunning 3D digital materials. Getting a grip on the ecosystem of apps can be challenging for beginners, which is where Realistic Asset Creation with Adobe Substance 3D comes in!This practical guide doesn't bombard you with reams of textual information. Instead, you get an interactive, project-based book that’ll help you gain sound knowledge of Adobe Substance 3D and set you on the right path toward a career in 3D design. You’ll start off with the rudiments of Adobe Substance 3D Painter, which will enable you to acquire the skills needed to work with layers, masks, shelves, textures, and more. Next, you’ll move on to Adobe Substance 3D Designer and become well-acquainted with this node-based design tool as you progress through the chapters. The final section is devoted to Adobe Substance 3D Stager, which teaches you to build complex 3D scenes and visualize your edits in real time.By the end of this Adobe book, you’ll have gained a solid understanding of Adobe Substance 3D and developed the skills to build a comprehensive portfolio of work, setting you up for a lucrative career in 3D design.

Learning Robotics Using Python. Bring robotics projects to life with Python! Discover how to harness everything from Blender to ROS and OpenCV with one of our most popular robotics books

Marek Suppa, Lentin Joseph

Learning Predictive Analytics with Python. Click here to enter text

Ashish Kumar

Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form - It needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Learning to predict who would win, lose, buy, lie, or die with Python is an indispensable skill set to have in this data age. This book is your guide to getting started with Predictive Analytics using Python. You will see how to process data and make predictive models from it. We balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and numpy. You’ll start by getting an understanding of the basics of predictive modeling, then you will see how to cleanse your data of impurities and get it ready it for predictive modeling. You will also learn more about the best predictive modeling algorithms such as Linear Regression, Decision Trees, and Logistic Regression. Finally, you will see the best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world.

Machine Learning: End-to-End guide for Java developers. Data Analysis, Machine Learning, and Neural Networks simplified

Boštjan Kaluža, Krishna Choppella, Uday Kamath

Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. In this course, we cover how Java is employed to build powerful machine learning models to address the problems being faced in the world of Data Science. The course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization. The next section has a detailed overview of statistical techniques, covering machine learning, neural networks, and deep learning. The next couple of sections cover applying machine learning methods using Java to a variety of chores including classifying, predicting, forecasting, market basket analysis, clustering stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, and deep learning.The last section highlights real-world test cases such as performing activity recognition, developing image recognition, text classification, and anomaly detection. The course includes premium content from three of our most popular books:[*]Java for Data Science[*]Machine Learning in Java [*]Mastering Java Machine LearningOn completion of this course, you will understand various machine learning techniques, different machine learning java algorithms you can use to gain data insights, building data models to analyze larger complex data sets, and incubating applications using Java and machine learning algorithms in the field of artificial intelligence.