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Python & AI For Dummies
Unlock the combined power of Python and AI to supercharge your next technical project and your career Python & AI For Dummies explores the exciting combo of two revolutionary technologies that are reshaping how we work, code, and solve problems. Authors John C. Shovic and Mary Everett draw on their extensive work in computer science, precision agriculture, and artificial intelligence to walk you through the intersection of Python programming and AI applications. No matter your professional background, learn how to use Python's versatility to unlock AI's transformative power. This guide offers hands-on approaches to implementing AI with Python. It moves from foundational concepts to advanced applications, covering essential Python libraries: TensorFlow, PyTorch, OpenCV, and scikit-learn. It also explores essential AI concepts, like neural networks, machine learning models, and natural language processing. Python & AI For Dummies is packed with hands-on projects and real-world examples, that explain how to build machine vision systems, create language models, implement reinforcement learning, and develop AI agents. Broken down into manageable, jargon-free lessons, explore topics from theoretical programming fundamentals to cutting-edge AI applications. Inside the book: Grasp fundamental AI concepts including machine learning, neural networks, and deep learning architecturesExplore eight essential Python libraries designed specifically for AI development and data manipulationBuild practical projects, including machine vision systems, large language models, and AI agentsLearn proven techniques for data preprocessing, model training, and avoiding common pitfalls like overfittingGain insights into emerging technologies including generative AI, transformers, and the Model Context Protocol A can’t-miss resource for programmers interested in expanding their AI skillset, professionals in finance or marketing who want to develop new capabilities, and small business owners ready to streamline their operations, Python & AI For Dummies offers step-by-step guidance, troubleshooting tips, and real-world applications in industries from manufacturing to agriculture.
R 750.00
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Deep Learning with Python, Third Edition
The bestselling book on Python deep learning, now covering generative AI, Keras 3, PyTorch, and JAX!Deep Learning with Python, Third Edition puts the power of deep learning in your hands. This new edition includes the latest Keras and TensorFlow features, generative AI models, and added coverage of PyTorch and JAX. Learn directly from the creator of Keras and step confidently into the world of deep learning with Python.In Deep Learning with Python, Third Edition you'll discover: Deep learning from first principlesThe latest features of Keras 3A primer on JAX, PyTorch, and TensorFlowImage classification and image segmentationTime series forecastingLarge Language modelsText classification and machine translationText and image generation—build your own GPT and diffusion models!Scaling and tuning models With over 100,000 copies sold, Deep Learning with Python makes it possible for developers, data scientists, and machine learning enthusiasts to put deep learning into action. In this expanded and updated third edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. You'll master state-of-the-art deep learning tools and techniques, from the latest features of Keras 3 to building AI models that can generate text and images.
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Python for Chemists
This accessible and self-contained guide provides a comprehensive introduction to the popular programming language Python, with a focus on applications in chemistry and chemical physics. Ideally suited to students and researchers of chemistry learning to employ Python for problem-solving in their research, this fast-paced primer first builds a solid foundation in the programming language before progressing to advanced concepts and applications in chemistry. The required syntax and data structures are established, and then applied to solve problems computationally. Popular numerical packages are described in detail, including NumPy, SciPy, Matplotlib, SymPy, and pandas. End of chapter problems are included throughout, with worked solutions available within the book. Additional resources, datasets, and Jupyter Notebooks are provided on a companion website, allowing readers to reinforce their understanding and gain confidence applying their knowledge through a hands-on approach.
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Learning Python: A Course in 16 Lessons for GCSE
This is an introductory text book that teaches Python programming. It is intended mainly for GCSE and IGCSE Computer Science students. It is a very practical book and assumes that the student knows little. The book starts by looking at the Python programming environment, then entering commands at the command prompt. Later on short programs,followed by longer programs. By the time the last chapter has been reached longer programs suitable for coursework are discussed. If used as a text book to learn programming, it is suggested that one lesson (chapter) from the book is studied each week. That way a student can learn Python in 4 months.
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Cracking Codes With Python
Cracking Secret Codes with Python is a hands-on introduction to Python that teaches readers how to make and hack cipher programs, which are used to encrypt secret messages. It covers ciphers like the Caesar cipher, transposition cipher, and the RSA cipher, and teaches readers how to test and hack them. For every program, Sweigart provides the full source code and then walks readers through it, explaining how every line works. Along the way, readers will learn Python fundamentals - and by the book's end, they'll have a solid foundation in Python and some fun programs under their belt.
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Python for Experimental Psychologists
Python for Experimental Psychologists equips researchers who have no prior programming experience with the essential knowledge to independently script experiments and analyses in the programming language Python. The book offers an excellent introduction, whether you are an undergraduate, a PhD candidate, or an established researcher.This updated edition is on Python 3 (the most current version). It starts by teaching the fundamentals of programming in Python, and then offers several chapters on scripting experiments (displaying stimuli, obtaining and logging user input, precision timing, etc.) using the popular PsychoPy package. The remainder of the book is dedicated to data analysis, and includes chapters on reading/writing to text files, time series, eye tracking, data visualisation, and statistics.Access to a companion website enriches the learning experience with colour figures, example stimuli, datasets, scripts, and a portable Windows installation of Python. The book assumes no prior knowledge, and its informal and accessible tone helps readers with backgrounds in experimental psychology and cognitive neuroscience to quickly understand Python. It serves as a useful resource not only for researchers in these fields, but also for lecturers instructing on methodology and data analysis.Python for Experimental Psychologists demystifies programming complexities, and empowers researchers to proficiently conduct experiments and to analyse their results.
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Python For ArcGIS
This book introduces Python scripting for geographic information science (GIS) workflow optimization using ArcGIS. It builds essential programming skills for automating GIS analysis. Over 200 sample Python scripts and 175 classroom-tested exercises reinforce the learning objectives. Readers will learn to: • Write and run Python in the ArcGIS Python Window, the PythonWin IDE, and the PyScripter IDE • Work with Python syntax and data types • Call ArcToolbox tools, batch process GIS datasets, and manipulate map documents using the arcpy package • Read and modify proprietary and ASCII text GIS data • Parse HTML web pages and KML datasets • Create Web pages and fetch GIS data from Web sources. • Build user-interfaces with the native Python file dialog toolkit or the ArcGIS Script tools and PyToolboxes Python for ArcGIS is designed as a primary textbook for advanced-level students in GIS. Researchers, government specialists and professionals working in GIS will also find this book useful as a reference.
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Python Programming for Data Analysis
This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of California, San Diego, which is a requirement for both graduate and undergraduate degrees in Machine Learning and Data Science. This book is ideal for readers with some Python programming experience. The book covers key language concepts that must be understood to program effectively, especially for data analysis applications. Certain low-level language features are discussed in detail, especially Python memory management and data structures. Using Python effectively means taking advantage of its vast ecosystem. The book discusses Python package management and how to use third-party modules as well as how to structure your own Python modules. The section on object-oriented programming explains features of the language that facilitate common programming patterns.After developing the key Python language features, the book moves on to third-party modules that are foundational for effective data analysis, starting with Numpy. The book develops key Numpy concepts and discusses internal Numpy array data structures and memory usage. Then, the author moves onto Pandas and details its many features for data processing and alignment. Because strong visualizations are important for communicating data analysis, key modules such as Matplotlib are developed in detail, along with web-based options such as Bokeh, Holoviews, Altair, and Plotly.The text is sprinkled with many tricks-of-the-trade that help avoid common pitfalls. The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis. To get the most out of this book, open a Python interpreter and type along with the many code samples.
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Python für Ingenieure für Dummies
Schlichtes Ausführen fertiger Software wird den Bedürfnissen des Ingenieuralltags nicht mehr gerecht. Oft muss Programmcode selbst entwickelt oder angepasst werden. Aber Ingenieure sind keine Softwareentwickler. Mit Python steht ein mächtiger und flexibler Werkzeugkasten zur Verfügung, der es erlaubt, eine große Klasse von Ingenieurproblemen - oft mit wenig Aufwand - zu lösen. Die Kernaufgaben sind dabei meist: Daten akquirieren, Lösungsalgorithmen anwenden, Ergebnisse visualisieren. Das Buch zeigt anhand zahlreicher Beispiele aus unterschiedlichen Anwendungsfeldern der Ingenieurwissenschaften, wie Python zur Lösung dieser Aufgaben eingesetzt werden kann. Gleichzeitig wird das nötige Hintergrundwissen vermittelt, um das Gelernte auf eigene Fragestellungen zu transferieren. Die vermittelten Kenntnisse sind anwendbar auf Übungsaufgaben im Studium genauso wie auf Probleme aus der Praxis.
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Optimizing Visual Studio Code for Python Development
Learn Visual Studio Code and implement its features in Python coding, debugging, linting, and overall project management. This book addresses custom scenarios for writing programs in Python frameworks, such as Django and Flask.The book starts with an introduction to Visual Studio Code followed by code editing in Python. Here, you will learn about the required extensions of Visual Studio Code to perform various functions such as linting and debugging in Python. Next, you will set up the environment and run your projects along with the support for Jupyter. You will also work with Python frameworks such as Django and go through data science specific-information and tutorials. Finally, you will learn how to integrate Azure for Python and how to use containers in Visual Studio Code.Optimizing Visual Studio Code for Python Development is your ticket to writing Python scripts with this versatile code editor.What You'll LearnExecute Flask development in Visual Studio Code for control over libraries used in an applicationOptimize Visual Studio Code to code faster and betterUnderstand linting and debugging Python code in Visual Studio CodeWork with Jupyter Notebooks in Visual Studio CodeWho This Book Is ForPython developers, beginners, and experts looking to master Visual Studio Code
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