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Item #:
90231392
Machine Learning with Python: A Practical Beginners’ Guide: 2 (Learn Machine Learning for Beginners)
85% of respondents would recommend this to a friend
Item #:
90231392
CHF 24
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What Stands Out
Beginner Friendly
This guide is designed specifically for beginners, making complex concepts accessible and easy to understand, allowing readers to build a solid foundation in machine learning.
Practical Applications
Focuses on real-world applications and hands-on projects, helping readers to immediately apply learned concepts and gain practical experience in machine learning with Python.
Comprehensive Coverage
Offers extensive coverage of essential machine learning topics, ensuring a well-rounded understanding and equipping readers with the necessary skills to tackle various challenges.
Product Details
| Publisher | Independently published |
| Publication date | 15 Oct. 2019 |
| Language | English |
| Print length | 186 pages |
| ISBN-10 | 1686658494 |
| ISBN-13 | 978-1686658495 |
| Item weight | 1.05 kg |
| Dimensions | 15.24 x 1.19 x 22.86 cm |
| Book 2 of 3 | Learn Machine Learning for Beginners |
Who Should Buy?
-
Beginners in ML
Ideal for individuals new to machine learning concepts and Python programming looking to build foundational knowledge.
-
Self-learners
Great for self-motivated learners who prefer a practical approach with hands-on examples and exercises.
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Students
Perfect for students in data science or computer science programs needing supplemental material for coursework.
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Advanced Users
Not suitable for experienced machine learning practitioners seeking in-depth or advanced algorithmic discussions and applications.
Product Description
Machine Learning with Python: A Practical Beginners’ Guide: 2 (Learn Machine Learning for Beginners)
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Statistics & Research Editorial Review
Machine Learning With Python A Practical Beginners Guide 2 Learn Machine Learning For Beginners is a fantastic resource that provides an excellent introduction to simple machine learning models along with practical coding exercises that help put theory into practice. Readers have praised its readability and understandable illustrations, making it suitable for beginners looking to navigate the complexities of machine learning. Although the book contains useful examples, some datasets referenced may no longer be available and could require additional effort to source. Overall, it effectively breaks down challenging concepts, ensuring that newcomers do not underestimate the intricacies of data mining and data science.
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Pros
- Readable and easy to follow for beginners
- Practical coding exercises enhance learning
- Illustrated examples make concepts clear
- Excellent introduction to machine learning models
- Encourages critical thinking about data science
Cons
- Setting up the development environment can be challenging
Product Price History
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Features & Benefits
- Practical guide for beginners to learn machine learning with Python.
- Includes step-by-step instructions for coding various prediction models.
- Focus on popular algorithms such as logistic regression and decision trees.
- Utilizes popular Python libraries: Pandas, Scikit-learn, Matplotlib, and Seaborn.
- Offers hands-on projects for applying learned skills.
- Perfect for those with basic knowledge looking to enhance their skill set.
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