Python for TensorFlow Pocket Primer. A Quick Guide to Python Libraries for TensorFlow Developers

Mercury Learning and Information, Oswald Campesato

As part of the best-selling *Pocket Primer* series, this book prepares programmers for machine learning and deep learning with TensorFlow. It begins with a quick introduction to Python, followed by chapters on NumPy, Pandas, Matplotlib, and scikit-learn. The final chapters provide TensorFlow 1.x code samples, including detailed examples for TensorFlow Dataset, crucial for TensorFlow 2.The journey starts with Python basics and progresses through essential data manipulation and visualization libraries. You'll explore machine learning fundamentals with scikit-learn before diving into TensorFlow, learning to construct data pipelines with TensorFlow Dataset APIs like map(), filter(), and batch().Understanding these concepts is vital for modern AI applications. This book transitions readers from basic programming to advanced machine learning and deep learning techniques, blending theory with practical skills. Companion files with source code enhance learning, making this an essential resource for mastering Python, machine learning, and TensorFlow.

Make Amazing Games. Game Design and Development Using Fusion 2.5: From Basics to Advanced

Mercury Learning and Information, Jason Darby

This course is designed for aspiring game developers with no prior experience or programming knowledge. It provides a step-by-step guide through the game creation process using drag-and-drop game creation software available on Steam. The course begins with basic game design concepts and an introduction to the Fusion software, progressing through various stages of game development.Understanding game development is essential for those who want to turn their creative ideas into playable games. This course covers the creation of four fully playable games: a platform game, a bat-and-ball game, a mouse-clicker game, and a side-scrolling shoot-'em-up game. By completing these projects, users will gain practical experience and confidence in their game development skills.The journey continues with advanced features such as porting games to the web, debugging, and publishing. The companion files include game demos, graphic libraries, and source code, providing all the resources needed to successfully create and distribute your games. This comprehensive guide ensures that by the end of the course, you will have the knowledge and skills to create and publish your own games.

CSS3 and SVG with GPT-4. Explore CSS3 animations and SVG techniques with GPT-4 insights

Mercury Learning and Information, Oswald Campesato

This book is your gateway to exploring the seamless integration of CSS3, SVG, and GPT-4. It begins by introducing the fundamentals of GPT-4 and generative AI, setting a solid foundation for understanding its capabilities. Alongside, you'll learn prompt engineering techniques to effectively interact with AI tools.The journey progresses into CSS3, covering its core principles and advanced features such as 3D animations. You'll discover innovative ways to integrate GPT-4 into web design processes, creating dynamic and visually engaging content. The book also delves into Scalable Vector Graphics (SVG), offering insights into creating scalable and crisp graphics. Combining SVG with GPT-4, you'll uncover new possibilities for unique designs.By the end, you'll have mastered the tools and techniques to harness AI-driven creativity, making your web development projects more efficient and imaginative. This book is perfect for designers, developers, and anyone looking to explore the intersection of AI and design.

Access 365 Project Book. Hands-On Database Creation

Mercury Learning and Information, Julitta Korol

This book is a practical introduction to building and managing Access desktop databases. Instead of merely explaining Microsoft Access, it helps you complete tasks related to creating, using, and managing a database. The hands-on approach focuses on creating a traditional Access desktop database and emphasizes splitting the database for optimized multi-user access. The primary project, the Employee Training Database (ETD), offers practical, real-world experience.The book guides you through database creation and management. It starts with planning and designing a database, followed by creating and setting up Access tables. It then covers primary keys, indexes, and table relationships, and populating tables with data. The middle sections include working with queries and designing and customizing forms.The latter part focuses on designing and using reports and customizing them. It concludes with compacting, splitting, and securing the database for optimized performance and security. These concepts enable efficient database management and enhance multi-user collaboration. This book transitions you from a novice to a proficient user, equipped with practical skills and comprehensive knowledge. Companion files with hands-on examples enrich your learning.

Computer Graphics Programming in OpenGL With C++ (Edition 3). Mastering 3D Graphics and Animation Techniques

Mercury Learning and Information, V. Scott Gordon, John L. Clevenger

This edition provides step-by-step instruction on modern OpenGL 4.0+ GLSL shader programming with C++, covering theoretical foundations of 3D computer graphics. Every shader stage is explored, from basics like modeling, textures, lighting, and shadows, to advanced techniques such as tessellation, noise maps, water, and stereoscopy. Expanded coverage includes camera control, refraction, and ray tracing with bounding volume hierarchies. Companion files include source code, shaders, model files, and skyboxes for all examples in the book.Understanding these concepts is crucial for creating sophisticated 3D graphics applications. The course begins with OpenGL basics and pipeline understanding, followed by mathematical foundations and managing 3D graphics data. It covers texture mapping, 3D models, lighting, shadows, enhancing surface detail, and advanced topics like parametric surfaces, tessellation, and geometry shaders. Final chapters delve into simulating water, ray tracing, and stereoscopy for 3D graphics.This book equips readers with the knowledge to master OpenGL programming and 3D graphics, making it invaluable for developers and enthusiasts aiming to advance their skills. The practical approach and comprehensive examples ensure thorough learning, bridging the gap between theory and real-world application.

Data Analytics. Master the Art of Data Analytics with Essential Tools and Techniques

Mercury Learning and Information, Christopher Greco

Data analytics is becoming increasingly important in our daily lives. This book offers a comprehensive view of data analytics skills, starting with a primer on statistics and progressing to the application of these methods. The text includes various formulas and algorithms used in data analytics, which can be applied in any software to achieve desired results. Through numerous demonstrations, it provides clear instruction on how to incorporate data analytics into critical thinking.The book covers a range of methods and techniques, supplemented with case studies specific to project managers, systems engineers, and cybersecurity professionals. Each profession can practice data analytics relevant to their fields. The main objective is to refresh statistical knowledge necessary for building data analytics models and to foster analytical thinking essential across these professions.From introducing statistics and data to reviewing central tendency measures and probability, the book moves to more complex topics like effect size, analysis methods, and data presentation. By the end of the course, readers will be well-versed in data analytics, ready to apply these skills effectively in their respective fields, enhancing decision-making and analytical thinking.

Python 3 for Machine Learning. Harness the Power of Python for Advanced Machine Learning Projects

Mercury Learning and Information, Oswald Campesato

This book introduces basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter covers fundamental machine learning concepts. The sixth chapter dives into machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on natural language processing (NLP) and reinforcement learning (RL). Keras-based code samples supplement the theoretical discussion.The course begins with Python basics, including conditional logic, loops, functions, and collections. It then explores data manipulation with NumPy and Pandas. The journey continues with an introduction to machine learning, focusing on essential concepts and classifiers. Advanced topics like NLP and RL are covered, ensuring a comprehensive understanding of machine learning.These concepts are crucial for developing machine learning applications. This book transitions readers from basic Python programming to advanced machine learning techniques, blending theory with practical skills. Appendices for regular expressions, Keras, and TensorFlow 2, along with companion files, enhance learning, making this an essential resource for mastering Python and machine learning.

Data Structures and Program Design Using Python. A Self-Teaching Introduction to Data Structures and Python

Mercury Learning and Information, D. Malhotra, N. Malhotra

This book, part of the Pocket Primer series, introduces the basic concepts of data science using Python 3 and other applications. It offers a fast-paced introduction to data analytics, statistics, data visualization, linear algebra, and regular expressions. The book features numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available.Understanding data science is crucial in today's data-driven world. This book provides a comprehensive introduction, covering key areas such as Python 3, data visualization, and statistical concepts. The practical code samples and hands-on approach make it ideal for beginners and those looking to enhance their skills.The journey begins with working with data, followed by an introduction to probability, statistics, and linear algebra. It then delves into Python, NumPy, Pandas, R, regular expressions, and SQL/NoSQL, concluding with data visualization techniques. This structured approach ensures a solid foundation in data science.