The Machine Learning Workshop - Second Edition: Get ready to develop your own high-performance machine learning algorith, (Paperback)
GHS 884
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With The Machine Learning Workshop, you'll master the scikit-learn library and become proficient in developing clever machine learning algorithms.
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- Take a comprehensive and step-by-step approach to understanding machine learningKey Features Discover how to apply the scikit-learn uniform API in all types of machine learning models Understand the difference between supervised and unsupervised learning models Reinforce your understanding of machine learning concepts by working on real-world examples Book Description Machine learning algorithms are an integral part of almost all modern applications. To make the learning process faster and more accurate, you need a tool flexible and powerful enough to help you build machine learning algorithms quickly and easily. With The Machine Learning Workshop, you'll master the scikit-learn library and become proficient in developing clever machine learning algorithms. The Machine Learning Workshop begins by demonstrating how unsupervised and supervised learning algorithms work by analyzing a real-world dataset of wholesale customers. Once you've got to grips with the basics, you'll develop an artificial neural network using scikit-learn and then improve its performance by fine-tuning hyperparameters. Towards the end of the workshop, you'll study the dataset of a bank's marketing activities and build machine learning models that can list clients who are likely to subscribe to a term deposit. You'll also learn how to compare these models and select the optimal one. By the end of The Machine Learning Workshop, you'll not only have learned the difference between supervised and unsupervised models and their applications in the real world, but you'll also have developed the skills required to get started with programming your very own machine learning algorithms. What you will learn Understand how to select an algorithm that best fits your dataset and desired outcome Explore popular real-world algorithms such as K-means, Mean-Shift, and DBSCAN Discover different approaches to solve machine learning classification problems Develop neural network structures using the scikit-learn package Use the NN algorithm to create models for predicting future outcomes Perform error analysis to improve your model's performance Who this book is for The Machine Learning Workshop is perfect for machine learning beginners. You will need Python programming experience, though no prior knowledge of scikit-learn and machine learning is necessary.
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | July, 2020 |
| Pages | 286 |
| Subgenre | Languages |
| Series title | No Series |
| Edition | 2nd Edition |
| Publisher | Packt Publishing |
| Original languages | English |
| Language | English |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.50 x 0.60 x 9.25 in (19.1 x 1.5 x 23.5 cm) |
| Assembled product weight | 1.09 lb (490 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
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Aspiring Data Scientists
Perfect for beginners wanting to gain practical experience in developing machine learning algorithms effectively.
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Intermediate Programmers
Ideal for those with programming experience looking to enhance their skills in machine learning techniques.
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Academic Students
Beneficial for students studying data science or machine learning as a supplemental resource for hands-on learning.
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Beginner Programmers
Not suitable for those with no coding experience, as it requires some programming knowledge to benefit fully.
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Hyatt Saleh All Books Editorial Review
The Machine Learning Workshop - Second Edition: Get ready to develop your own high-performance machine learning algorithm is an essential paperback for anyone interested in computing. With 286 pages of insightful content published by Packt Publishing in July 2020, this non-fiction book explores the intricacies of machine learning algorithms. Readers appreciate the clear explanations and practical approach, making it an excellent resource for both beginners and experienced practitioners in the field. This edition focuses on high-performance algorithms, guiding readers through hands-on projects that enhance their understanding of machine learning concepts.
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Pros
- Informative content for developing machine learning algorithms
- Clear explanations suitable for all skill levels
- Hands-on projects to reinforce learning
- Well-structured chapters for easy navigation
- Updated second edition with the latest techniques
Cons
- Some readers might prefer more advanced topics
Product Price History
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GHS 884
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Features & Benefits
- Comprehensive, step-by-step guide to machine learning.
- Learn to use the scikit-learn library effectively.
- Hands-on experience with real-world datasets.
- Covers both supervised and unsupervised learning models.
- Develop neural networks and optimize performance.
- Ideal for beginners with Python programming experience.
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