Machine Learning with Python: Basic Concepts - Classification Regression - Clustering Paper Cover – January 1, 2024
XPF 3453
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This book deals with all aspects of machine learning, enriched with applications for solving real-world problems in Python.
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What Stands Out
Product Details
| Publishers | Distinguished Publishing |
| Date of publicization | January 1, 2024 |
| Language | Turkish |
| Print length | 516 pages |
| ISBN-10 | 9750290275 |
| ISBN-13 | 978-9750290275 |
| Dimensions | 1 x 16 x 24 cm |
Who Should Buy?
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Beginners in ML
Ideal for individuals new to machine learning seeking foundational knowledge in Python applications.
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Students of Data Science
Perfect resource for data science students looking to understand core concepts through practical examples and exercises.
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Professionals Upskilling
Great for professionals wanting to enhance their skill set or transition into data-centric roles through machine learning.
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Advanced Practitioners
Not suitable for those with advanced machine learning experience seeking in-depth exploration of complex algorithms.
Product Description
Machine Learning with Python: Basic Concepts - Classification Regression - Clustering Paper Cover – January 1, 2024
Customer Questions & Answers
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Question:
What topics are covered in the book?
Answer: The book covers basic concepts in machine learning, model creation, evaluation, supervised and unsupervised learning algorithms, and more. -
Question:
Is this book featureable for beginners?
Answer: Yes, the simple narrative makes it accessible to university students and readers of all ages interested in machine learning. -
Question:
Is this book part of a series?
Answer: Yes, it is the second book in a three-book series on Artificial Intelligence.
Ömer Deperlioğlu , Utku Köse Editorial Review
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XPF 3453
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Features & Benefits
- Comprehensive coverage of machine learning basics.
- Practical applications for real-world problem solving in Python.
- Easy-to-understand narrative suitable for all ages.
- Includes supervised, unsupervised, and reinforcement learning algorithms.
- Detailed discussions on model creation, evaluation, and data science.
- Part of a three-book series on Artificial Intelligence.
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