Prompt Detail:
Sure, here is a table of chapter, section, and summarized bullet points for the book "Machine Learning Design Patterns: Solutions to common challenges in data, Model Building, and MLOps" by Valliappa Lakshmanan:
| Chapter | Section | Summary |
|---|---|---|
| 1 | Introduction to Machine Learning Design Patterns | Introduces the concept of machine learning design patterns and their importance in developing scalable and reliable ML systems. |
| 2 | Data Patterns | Covers patterns related to data acquisition, data preprocessing, and data validation. Includes patterns for handling missing data, dealing with imbalanced datasets, and data versioning. |
| 3 | Model Building Patterns | Covers patterns related to model selection, feature engineering, and hyperparameter tuning. Includes patterns for ensemble learning, transfer learning, and model explainability. |
| 4 | MLOps Patterns | Covers patterns related to model deployment, monitoring, and governance. Includes patterns for continuous integration and delivery, A/B testing, and model performance monitoring. |
| 5 | Case Studies | Provides real-world case studies that demonstrate how the patterns covered in the book can be applied in practice. Includes case studies from various industries, including healthcare, finance, and e-commerce. |
| 6 | Conclusion | Summarizes the key takeaways from the book and provides recommendations for further reading. |
I hope you find this helpful! Let me know if you have any further questions.
Add a comment
Add to Chrome - It's free
Add to Firefox - It's free
Add to Edge - It's free