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Python for Machine Learning: Implement ML Models with Scikit-Learn
Paperback
Publisher: Independently Published
Published: Dec 14 2024
Pages: 218
Weight: 0.66
Height: 0.46 Width: 6.00 Depth: 9.00
Language: English
No more theoretical jargon - learn through hands-on projects, including sentiment analysis, customer segmentation, and predictive maintenance. Each chapter builds your expertise with industry-standard practices and optimization techniques. Perfect For
- Python developers ready to level up their ML skills
- Data analysts transitioning to machine learning
- Students seeking practical ML implementation skills Key Features Modern Techniques Master the latest scikit-learn features, including pipeline optimization, automated ML workflows, and model evaluation strategies. Learn to fine-tune hyperparameters and build ensemble models that outperform traditional approaches. Real-World Applications Transform raw data into valuable insights using production-ready code. Implement advanced techniques for feature engineering, cross-validation, and model selection that actually work in business environments.
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