Programming Fundamentals Using MATLAB. Master the Basics and Beyond of MATLAB Programming

Mercury Learning and Information, Michael Weeks

This book introduces MATLAB syntax and environment, ideal for beginners with no programming background. The first four chapters cover basic programming concepts, computing terminology, MATLAB syntax, control structures, operators, arrays, and matrices. Next, the book explores grouping data, working with files, creating images, building graphical user interfaces, experimenting with sound, and debugging. The final chapters present case studies on using MATLAB with tools like Arduino, Linux, Git, and Mex, essential for basic programming knowledge.Understanding MATLAB is crucial for data analysis and technical computing. This book transitions readers from basics to advanced topics, blending theoretical knowledge with practical applications. Companion files with code and four-color figures enhance learning, making this an essential resource for mastering MATLAB.

Prompt Engineering Using ChatGPT. Crafting Effective Interactions and Building GPT Apps

Mercury Learning and Information, Mehrzad Tabatabaian

This book is designed for mastering prompt engineering in artificial intelligence, focusing on ChatGPT, GPT-4, and GPT plug-ins. It explores fundamental principles, practical techniques, and real-world applications. Readers will learn the role of prompts in AI interactions, the anatomy of well-constructed prompts, and various prompt styles. The book also covers setting constraints to guide AI responses and ensure ethical interactions, making it ideal for both beginners and advanced users.The journey begins with the foundations of prompts and crafting contextual prompts. It progresses to asking specific questions, providing constraints, and creating diverse content prompts. Advanced chapters cover debugging, iterating prompts, and using GPT-4 with plug-ins. The book concludes with real-world applications, future trends, and ethical considerations, ensuring a comprehensive understanding of prompt engineering.Understanding these concepts is crucial for effective AI interactions. This book transitions readers from basic to advanced prompt engineering, blending theoretical knowledge with practical skills. It is an essential resource for mastering prompt engineering and building innovative GPT applications.

Python 3 and Data Analytics Pocket Primer. A Quick Guide to NumPy, Pandas, and Data Visualization

Mercury Learning and Information, Oswald Campesato

This book, part of the best-selling Pocket Primer series, introduces readers to the fundamental concepts of data analytics using Python 3. The course begins with a concise introduction to Python, covering essential programming constructs and data manipulation techniques. This foundation sets the stage for deeper dives into data analytics, emphasizing the importance of data cleaning, a critical step in any data analysis process.Following the Python basics, the course explores powerful libraries such as NumPy and Pandas for efficient data handling and manipulation. It then delves into statistical concepts, providing the necessary background for understanding data distributions and analytical methods. The course culminates in data visualization techniques using Matplotlib and Seaborn, demonstrating how to effectively communicate insights through graphical representations.Throughout the course, numerous code samples and practical examples are provided, reinforcing learning and offering hands-on experience. Companion files with source code and figures are available online, supporting the learning journey. This comprehensive guide equips both beginners and seasoned professionals with the skills needed to excel in data analytics.

Python 3 and Data Visualization. Mastering Graphics and Data Manipulation with Python

Mercury Learning and Information, Oswald Campesato

Python 3 and Data Visualization provides an in-depth exploration of Python 3 programming and data visualization techniques. The course begins with an introduction to Python, covering essential topics from basic data types and loops to advanced constructs such as dictionaries and matrices. This foundation prepares readers for the next section, which focuses on NumPy and its powerful array operations, seamlessly leading into data visualization using prominent libraries like Matplotlib.Chapter 6 delves into Seaborn's rich visualization tools, providing insights into datasets like Iris and Titanic. The appendix covers additional visualization tools and techniques, including SVG graphics and D3 for dynamic visualizations. The companion files include numerous Python code samples and figures, enhancing the learning experience.From foundational Python concepts to advanced data visualization techniques, this course serves as a comprehensive resource for both beginners and seasoned professionals, equipping them with the necessary skills to effectively visualize data.

Python 3 and Machine Learning Using ChatGPT / GPT-4. Harness the Power of Python, Machine Learning, and Generative AI

Mercury Learning and Information, Oswald Campesato

This book bridges the gap between theoretical knowledge and practical application in Python programming, machine learning, and using ChatGPT-4 in data science. It starts with an introduction to Pandas for data manipulation and analysis. The book then explores various machine learning classifiers, from kNN to SVMs. Later chapters cover GPT-4's capabilities, enhancing linear regression analysis, and using ChatGPT in data visualization, including AI apps, GANs, and DALL-E.The journey begins with mastering Pandas and machine learning fundamentals. It progresses to applying GPT-4 in linear regression and machine learning classifiers. The final chapters focus on using ChatGPT for data visualization, making complex results accessible and understandable.Understanding these concepts is crucial for modern data scientists. This book transitions readers from basic Python programming to advanced applications of ChatGPT-4 in data science. Companion files with source code, datasets, and figures enhance learning, making this an essential resource for mastering Python, machine learning, and AI-driven data visualization.

Python 3 Data Visualization Using ChatGPT / GPT-4. Master Python Visualization Techniques with AI Integration

Mercury Learning and Information, Oswald Campesato

This book teaches Python 3 programming and data visualization, exploring cutting-edge techniques with ChatGPT/GPT-4 for generating compelling visuals. It starts with Python essentials, covering basic data types, loops, functions, and advanced constructs like dictionaries and matrices. The journey progresses to NumPy's array operations and data visualization using libraries such as Matplotlib and Seaborn. The book also covers tools like SVG graphics and D3 for dynamic visualizations.The course begins with foundational Python concepts, moves into NumPy and data visualization with Pandas, Matplotlib, and Seaborn. Advanced chapters explore ChatGPT and GPT-4, demonstrating their use in creating data visualizations from datasets like the Titanic. Each chapter builds on the previous one, ensuring a comprehensive understanding of Python and visualization techniques.These concepts are crucial for Python practitioners, data scientists, and anyone in data analytics. This book transitions readers from basic Python programming to advanced data visualization, blending theoretical knowledge with practical skills. Companion files with code, datasets, and figures enhance learning, making this an essential resource for mastering Python and data visualization.

Python 3 Data Visualization Using Google Gemini. Unlock the Power of Python and Google Gemini for Stunning Data Visualizations

Mercury Learning and Information, Oswald Campesato

This book teaches Python 3 programming and data visualization, exploring cutting-edge techniques with ChatGPT/GPT-4 for generating compelling visuals. It starts with Python essentials, covering basic data types, loops, functions, and advanced constructs like dictionaries and matrices. The journey progresses to NumPy's array operations and data visualization using libraries such as Matplotlib and Seaborn. The book also covers tools like SVG graphics and D3 for dynamic visualizations.The course begins with foundational Python concepts, moves into NumPy and data visualization with Pandas, Matplotlib, and Seaborn. Advanced chapters explore ChatGPT and GPT-4, demonstrating their use in creating data visualizations from datasets like the Titanic. Each chapter builds on the previous one, ensuring a comprehensive understanding of Python and visualization techniques.These concepts are crucial for Python practitioners, data scientists, and anyone in data analytics. This book transitions readers from basic Python programming to advanced data visualization, blending theoretical knowledge with practical skills. Companion files with code, datasets, and figures enhance learning, making this an essential resource for mastering Python and data visualization.

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.