Python Machine Learning: Learn Python in a Week and Master It. An Hands-On Introduction to Artificial Intelligence Coding, a Project-Based Guide with Practical Exercises (7 Days Crash Course)
Python Machine Learning: Learn Python in a Week and Master It. An Hands-On Introduction to Artificial Intelligence Coding, a Project-Based Guide with Practical Exercises (7 Days Crash Course)
The best solution is to follow a complete programming manual with hands-on projects and practical exercises.
Python Machine Learning: Learn Python in a Week and Master It. An Hands-On Introduction to Artificial Intelligence Coding, a Project-Based Guide with Practical Exercises (7 Days Crash Course)
Artikelnr.: 88729347

Python Machine Learning: Learn Python in a Week and Master It. An Hands-On Introduction to Artificial Intelligence Coding, a Project-Based Guide with

Artikelnr.: 88729347

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Besondere Merkmale

Rapid Learning
Condenses essential Python machine learning concepts into a one-week format, enabling learners to quickly grasp and apply knowledge in practical scenarios.
Hands-On Approach
Focuses on practical exercises and real-world projects, ensuring that readers gain valuable coding experience in artificial intelligence through active engagement and application.
Comprehensive Coverage
Offers a complete introduction to Python and machine learning, making it ideal for beginners and those seeking a structured way to enhance their coding skills effectively.

Produktdetails

Shop Python Machine Learning: Learn Python in a Week and Master It. An Hands-On Introduction to Artificial Intelligence Coding, a Project-Based Guide with Practical Exercises (7 Days Crash Course) online at a best price in Austria. 1914185099
  • Would you like to learn how to use Python to generate machine learning models but you think it would be too difficult? Or perhaps you want to automate simple things with your computer but you don't know how to do it?Here's the deal... As a beginner you might think that programming is complex... Learning artificial intelligence coding can take months, and the possibility to give up before mastering it could be high. So, if you have a project to develop you could think on hiring a professional developer to shorten the time. This may seem like a good solution but it is certainly very expensive and if the developer you chose doesn't perform a proper job you still have to pay for it.The best solution is to follow a complete programming manual with hands-on projects and practical exercises. Computer Programming Academy structured this guide as a course with seven chapters for seven days and studied special exercises for each section to apply what you have learned step-by-step. This protocol, tested on both total beginners and people who were already familiar with coding, takes advantage of the principle of diving, concentrating learning in one week. The result of this method has been one for both categories of students: the content of the course was learned faster and remembered longer respect the average.Inside this book, you will go through a first section in which fundamental and basic notions of deep learning are discussed, to get to the next chapters crafted specifically to help you learn advanced coding concepts required to develop training data sets for the production of successful machine learning models.In the detail, you will learn: Why Python is considered the fundamental tool for machine learningDeep understanding of the significance of machine learning in our daily lives and why you cannot ignored its importance in 202012 machine learning models that you must study as a beginnerThe most common mistakes to avoid when you start building machine learning models with PythonStep-by-step instructions to install required packages to set up a machine learning coding environmentThe algorithms that will make your life easier while coding artificial intelligenceA proven strategy to process raw data to generate high quality training data setsA simple method to build the desired machine learning model in less than 7 daysThe 2 main libraries you need implementing to develop a neural networkExercises and quizzes at the end of every chapter to review immediately what you've learnedExtra content that you will appreciate as curious technology enthusiastWhy is this book different? Most of the books on the market only take a brief look into machine learning, showing some of the topics but never going deep concretely. The best way to learn machine learning with Python is by doing and with this manual you will work through applicable projects in order to solidify your knowledge and obtain a huge sense of achievement.This is what this guide offers to you, even if you're completely new to programming in 2020 or you are just looking to widen your skills as programmer.Would You Like To Know More?Scroll up to the top of the page and select the BUY NOW button. The key to become a Python master is one click away!
Publisher Wiomy Ltd
Publication date November 10, 2020
Language English
Print length 212 pages
ISBN-10 1914185099
ISBN-13 978-1914185090
Item Weight 10.2 ounces (289.17 grams)
Dimensions 6 x 0.45 x 9 inches (15.2 x 1.1 x 22.9 cm)
Book 2 of 3 Learn Python

Für wen ist das Produkt geeignet?

Suitable For
  • Beginners in Programming

    Ideal for those new to coding and want a straightforward introduction to Python and machine learning concepts.

  • AI Enthusiasts

    Perfect for individuals interested in artificial intelligence who seek practical knowledge through project-based learning.

  • Time-Constrained Learners

    Suited for busy individuals wishing to learn Python quickly through intensive, focused study and hands-on exercises.

Not Suitable For
  • Experienced Programmers

    Not suitable for those who already have substantial programming skills and are looking for advanced machine learning content.

PRODUKTBESCHREIBUNG

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Kundenfragen und -antworten

  • Frage: What is the main focus of the book 'Python Machine Learning: Learn Python in a Week and Master It'?

    Antworten: The primary focus of this book is to teach readers the fundamental concepts of Python programming and machine learning within a hands-on, project-based context. It emphasizes practical implementation, allowing readers to work through projects that integrate artificial intelligence coding. This not only helps in solidifying programming skills but also in understanding real-world applications of machine learning, making it ideal for beginners or those looking to quickly upskill in these areas.
  • Frage: Who can benefit from reading this book?

    Antworten: This book is designed for a wide audience, including beginners with no prior programming experience and individuals who have some knowledge of Python but want to delve deeper into machine learning. Students, professionals in the tech industry, and hobbyists interested in artificial intelligence will particularly find this guide useful. Its hands-on approach equips readers with practical skills through real-world projects, making it applicable for those looking to enhance their career prospects or personal projects.
  • Frage: What programming language does the book focus on?

    Antworten: The book focuses on Python as the primary programming language for machine learning. Python is chosen for its simplicity and versatility, making it the preferred language in the data science and machine learning communities. Readers will learn to use Python libraries such as Pandas, NumPy, and Scikit-learn, enabling them to execute complex data analysis and implement machine learning algorithms effectively. This makes the book particularly valuable for anyone looking to engage in AI programming using a widely-used language.
  • Frage: What types of projects can I expect to work on?

    Antworten: Readers can expect to work on a variety of engaging projects that highlight different aspects of machine learning and artificial intelligence. These may include creating predictive models, data visualizations, and even simple neural networks. Through these practical projects, readers gain a robust understanding of how machine learning algorithms function, how to preprocess data, and how to evaluate model performance. This experiential learning process is ideal for developing solid programming and analytical skills in machine learning.
  • Frage: Is prior knowledge of machine learning required?

    Antworten: No prior knowledge of machine learning is necessary to benefit from this book. It starts with the basics of Python programming before gradually introducing machine learning concepts. The authors provide clear explanations and step-by-step instructions, making it accessible for newcomers. This gradual approach ensures that even complete beginners can follow along and build confidence, allowing them to master machine learning applications over time.
  • Frage: How does the book handle complex topics in machine learning?

    Antworten: The book simplifies complex machine learning topics by breaking them down into smaller, manageable sections. It combines theory with practical example projects, allowing readers to see concepts in action, which makes it easier to understand difficult subjects like regression analysis and neural networks. This method of combining theoretical foundations with practical application ensures that readers can grasp complex ideas without feeling overwhelmed, fostering a deeper understanding of machine learning.
  • Frage: What kind of reader would find this book most useful?

    Antworten: This book is particularly useful for aspiring data scientists, software engineers, or anyone interested in overarching AI concepts. It's also suited for professionals looking to pivot into data-driven roles. Those with a foundational knowledge of programming—whether as part of their academic study or in a professional context—will find the content directly applicable to their existing skills. Its project-focused approach also attracts hobbyists eager to apply machine learning techniques in personal projects.
  • Frage: Can this book help with job preparedness in the tech industry?

    Antworten: Yes, this book is an excellent resource for job preparedness in the tech industry, specifically in roles related to data science, machine learning, and AI development. By emphasizing practical, hands-on projects, readers build a portfolio of work that can demonstrate their skills to potential employers. Moreover, the knowledge and skills built through this book can give readers a competitive advantage when applying for roles in this growing field, particularly in positions that demand practical programming expertise.
  • Frage: Does the book provide resources for further learning?

    Antworten: While the book offers a comprehensive foundation in machine learning and Python programming, it also encourages readers to explore further resources online. This may include participating in coding communities, accessing supplementary online courses, and reviewing research papers. The hands-on projects and tutorials enhance the learning experience, and readers are directed to additional materials that expand their knowledge and keep them up to date with the latest in machine learning advancements.
  • Frage: Where can I buy 'Python Machine Learning: Learn Python in a Week and Master It'?

    Antworten: You can purchase 'Python Machine Learning: Learn Python in a Week and Master It' from Ubuy in Austria. Ubuy offers a seamless shopping experience with easy navigation, ensuring you can find and order the book swiftly. As a reliable platform, Ubuy is known for its extensive selection of books and resources, making it an excellent choice for acquiring this educational guide.

Python Editorial Review

Python Machine Learning: Learn Python in a Week and Master It. An Hands-On Introduction to Artificial Intelligence Coding, a Project-Based Guide with Practical Exercises (7 Days Crash Course) offers a glimpse into the fundamentals of machine learning, although user experiences vary widely. While some readers appreciated the structured introduction and praised it as suitable for beginners, others lamented the lack of hands-on exercises and poor writing quality, which detracted from their learning experience. It's worth noting that the book is labeled as a supplement to other texts, which may lead to some confusion. Despite its flaws, those committed to learning independently might find value in the content provided.

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Vorteile

  • Well-organized and easy for beginners to follow
  • Introduces key machine learning concepts clearly
  • Detailed explanations of coding principles
  • Potential for self-learners to grasp Python basics
  • Includes examples for applied learning

Nachteile

  • Some may find the writing distracting and unrefined

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