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Item #:
230615319
LEARN Scikit-Learn: Essential Machine Learning for Data Science (AI & Machine Learning ENG)
87% of respondents would recommend this to a friend
Item #:
230615319
JPY 4574
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What Stands Out
Comprehensive Coverage
This course provides in-depth insights into Scikit-Learn, covering essential machine learning techniques, best practices, and real-world applications, making it perfect for data science enthusiasts at any level.
Hands-On Projects
Engage in practical, hands-on projects that reinforce learning. This interactive approach ensures that learners can apply theoretical knowledge to solve real data science problems effectively.
Expert Instruction
Learn from industry experts with extensive machine learning experience, ensuring that the material is not only relevant but also up-to-date with the latest advancements in AI and machine learning.
Product Details
- LEARN Scikit-Learn: Essential Machine Learning for Data ScienceThis book is the key to mastering Scikit-Learn and building market-ready Machine Learning projects. Ideal for professionals and students who seek fast, direct, and applicable results. Learn high-impact techniques, design intelligent solutions, and boost your career in data science.Includes:• Quick setup of a productive environment with Python and Scikit-Learn• Data preprocessing and full pipeline automation• Fine-tuning models with cross-validation and hyperparameters• Practical application of regression, classification, and clustering• Model deployment integrated with Big Data and MLOps environmentsMaster the most widely used algorithms in the market and accelerate your entry into data science projects with Scikit-Learn.scikit-learn, machine learning, data science, smart pipelines, model automation, cross-validation, machine learning deployment, big data integration, mlops, spark
| Publisher | Independently published |
| Publication date | April 25, 2025 |
| Language | English |
| Print length | 196 pages |
| ISBN-13 | 979-8281460545 |
| Item Weight | 12.5 ounces (354.38 grams) |
| Dimensions | 6.24 x 0.64 x 9.24 inches (15.8 x 1.6 x 23.5 cm) |
| Part of series | AI & Machine Learning ENG |
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