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Machine Learning for Beginners: Learn to Build Machine Learning Systems Using Python (English Edition)
75% of respondents would recommend this to a friend
BDT 5654
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This book covers important concepts and topics in Machine Learning. It begins with Data Cleansing and presents an overview of Feature Selection. It then talks about training and testing, cross-validation, and Feature Selection.
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Product Details
| Publisher | BPB Publications |
| Publication date | August 21, 2020 |
| Language | English |
| Print length | 262 pages |
| ISBN-10 | 9389845424 |
| ISBN-13 | 978-9389845426 |
| Item Weight | 1.01 pounds (460 grams) |
| Dimensions | 7.5 x 0.6 x 9.25 inches (19.1 x 1.5 x 23.5 cm) |
Who Should Buy?
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Aspiring Data Scientists
Ideal for individuals looking to start a career in data science with practical tools and methods.
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Programming Enthusiasts
Great for those with a Python background who want to explore machine learning concepts in depth.
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Students and Learners
Perfect for students seeking introductory resources to understand machine learning and its applications.
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Advanced Practitioners
Not suitable for experienced data scientists who require in-depth, complex methodologies beyond foundational principles.
Product Description
Machine Learning for Beginners: Learn to Build Machine Learning Systems Using Python (English Edition)
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Python Editorial Review
Machine Learning for Beginners: Learn to Build Machine Learning Systems Using Python English Edition is an insightful book that offers a beginner's guide to building machine learning systems using Python. The author, Mr Bhasin, has done an excellent job of explaining the topic in a clear, concise, and easy-to-understand manner. This book not only covers general to advanced topics of machine learning, but it also explains the working of algorithms with the help of required mathematics and implementation of algorithms in Python. The book is a must-read for both beginner and experienced machine learning professionals who want to brush up their concepts. With a good balance of theory and practical implementation, the book provides an excellent resource for individuals who want to learn about machine learning.
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Pros
- Clear, concise, and easy-to-understand manner
- Good balance of theory and practical implementation
- Covers general to advanced topics of machine learning
- Explains the working of algorithms with the help of required mathematics and implementation of algorithms in Python
Cons
- One review mentioned that the book felt like a random class notes and suggested improvements in quality and content
Product Price History
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BDT 5654
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Features & Benefits
- Learn important concepts and topics in Machine Learning.
- Get an overview of Feature Selection and Data Cleansing
- Learn about training and testing, and cross-validation
- Covers common Classification and Regression techniques
- Explains implementation of Neural Networks and Support Vector Machines
- Includes techniques in Unsupervised Learning
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