Скачать или смотреть Caterpillar Shows How to Master the End-to-End Machine Learning Model Building Process (Preview)

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Paril Ghori, Senior Data Scientist at Caterpillar, presents the “Mastering the End-to-end Machine Learning Model Building Process: Best Practices and Pitfalls” tutorial at the May 2025 Embedded Vision Summit.

In this talk, Ghori explores the complete machine learning model building process, providing data scientists and ML engineers with practical insights and strategies for success. He examines each phase of the model life cycle, from data ingestion and pre-processing to feature engineering, model selection, training and fine-tuning. He explains best practices for model evaluation, validation and deployment, including effective MLOps integration to ensure seamless model monitoring and scalability.

Ghori highlights real-world case studies and common pitfalls encountered during model development, offering actionable solutions and strategies to overcome challenges. He emphasizes optimizing workflows to improve performance and ensure reproducibility in complex projects. You’ll gain a deeper understanding of the entire model building process and gain insights that will help you build robust, efficient and scalable models to drive impactful business outcomes and support continuous innovation.