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91464453
Ultimate Machine Learning with Scikit-Learn: Unleash the Power of Scikit-Learn and Python to Build Cutting-Edge Predictive Modeling Applications and
Item #:
91464453
CZK 1239
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What Stands Out
Comprehensive Coverage
Offers in-depth insights into Scikit-Learn's functionalities, making it perfect for both beginners and advanced users eager to master predictive modeling techniques.
Practical Applications
Focuses on real-world use cases, empowering learners to apply machine learning concepts effectively in various industries, enhancing career opportunities in the data science field.
Expert Guidance
Written by experienced professionals, this resource provides valuable tips and best practices, ensuring readers can navigate complex modeling challenges confidently and efficiently.
Product Details
| Publisher | Orange Education Pvt. Ltd |
| Publication date | May 6, 2024 |
| Language | English |
| Print length | 395 pages |
| ISBN-10 | 8197223947 |
| ISBN-13 | 978-8197223945 |
| Item Weight | 1.87 pounds (850 grams) |
| Dimensions | 7.5 x 0.89 x 9.25 inches (19.1 x 2.3 x 23.5 cm) |
| Book 2 of 2 | Machine Learning Engineer (ML) u2014 Advanced Path |
Product Description
Ultimate Machine Learning with Scikit-Learn: Unleash the Power of Scikit-Learn and Python to Build Cutting-Edge Predictive Modeling Applications and ... Learning Engineer (ML) Advanced Path)
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CZK 1239
This product is not Fulfilled by Ubuy and can take minimum 10 days in delivery. We might cancel the product from the order and refund you if any issue arise with the delivery of this product.
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Features & Benefits
- Master essential data preprocessing and modeling techniques for robust analysis.
- Learn predictive modeling applications using real-world tools and scenarios.
- Discover advanced methods for handling unstructured data and time series analysis.
- Gain practical insights into machine learning pipelines and ensemble methods.
- Designed for developers, students, and professionals looking for comprehensive learning.
- Includes easy-to-follow explanations and code samples in Python with Scikit-Learn.
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