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Python Machine Learning By Example: The easiest way to get into machine learning
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Yuxi (Hayden) Liu is an author of a series of machine learning books and an education enthusiast.
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Detalji o proizvodu
- Learn the fundamentals of machine learning and build your own intelligent applications
- Master the art of building your own machine learning systems with practical examples
- Work with important classification and regression algorithms and other machine learning techniques
- Explore data manipulation, visualization, and feature extraction using Python
- Implement machine learning models from scratch and evaluate their performance
- Solve real-world problems using machine learning and Python
| Publisher | Packt Publishing |
| Publication date | May 31, 2017 |
| Language | English |
| Print length | 254 pages |
| ISBN-10 | 1783553111 |
| ISBN-13 | 978-1783553112 |
| Item Weight | 15.5 ounces (439.43 grams) |
| Dimensions | 7.5 x 0.58 x 9.25 inches (19.1 x 1.5 x 23.5 cm) |
Who Should Buy?
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Beginners in ML
Ideal for individuals new to machine learning, providing practical examples for easier understanding.
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Practitioners Seeking Examples
Great for those who prefer learning by doing, with actionable insights through real-world examples.
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Python Enthusiasts
Perfect for Python users wanting to integrate machine learning into their skill set seamlessly.
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Advanced Users
Not suitable for experienced machine learning practitioners looking for deeper, theoretical insights or advanced topics.
OPIS PROIZVODA
Python Machine Learning By Example: The easiest way to get into machine learning
About This Item
Introducing "Python Machine Learning By Example: The easiest way to get into machine learning" Are you new to the world of machine learning and looking for a comprehensive guide to get started? Look no further! "Python Machine Learning By Example" is the perfect resource for beginners who want to dive into the exciting field of machine learning. Authored by Yuxi (Hayden) Liu, a renowned machine learning expert and best-selling author, this book is your go-to guide to learn the ins and outs of machine learning using Python. With his vast experience in the field, Hayden has developed a practical and easy-to-understand approach to help you grasp the concepts and techniques of machine learning. This book is not just another theoretical study of machine learning algorithms. It goes beyond that by providing real-life examples and projects that will help you apply what you have learned in a practical way.
From beginner-friendly tutorials to hands-on projects, you will get a chance to build your own machine learning applications and gain valuable insights into the world of data-driven decision making. Whether you are a programmer, data scientist, or simply an AI enthusiast, "Python Machine Learning By Example" has something for everyone. It covers a wide range of topics, including: - Python machine learning libraries: Explore popular Python libraries like Scikit-learn and TensorFlow to implement machine learning algorithms. - Machine learning techniques: Learn fundamental and advanced machine learning techniques such as clustering, classification, and regression. - Machine learning frameworks: Get familiar with popular machine learning frameworks like Keras and PyTorch to build deep learning models. - Machine learning applications: Discover real-world applications of machine learning, from image recognition to natural language processing. By the end of this book, you will have a solid foundation in machine learning and be able to apply your newfound knowledge to real-world scenarios. Whether you are interested in pursuing a career in machine learning or simply want to enhance your skills, "Python Machine Learning By Example" is a must-have resource. Don't miss this opportunity to learn machine learning from a renowned expert.
Grab your copy of "Python Machine Learning By Example" now and embark on an exciting journey into the world of machine learning!.
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Značajke i prednosti
- Bestselling author of Python Machine Learning by Example
- Experienced machine learning scientist
- Developed ad bidding and targeting algorithms
- Published IEEE papers during master's research
- Software Engineer, Machine Learning at Google
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