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Explore how AWS SageMaker can revolutionize machine learning implementations in the financial technology sector through this 30-minute conference talk from Conf42 Golang 2025. Discover the unique challenges facing FinTech companies when implementing machine learning solutions and learn how AWS SageMaker addresses these obstacles with its comprehensive suite of features and benefits. Dive into practical aspects of data preparation using SageMaker's tools, understand the model development and training processes, and examine various deployment options available for production environments. Gain insights into leveraging the Go programming language for machine learning applications within the FinTech domain, and review real-world use cases and success stories that demonstrate the platform's effectiveness. The presentation covers the complete machine learning lifecycle from data preparation through model deployment, providing actionable knowledge for accelerating innovation in financial technology applications using cloud-based machine learning services.
Syllabus
00:00 Introduction to FinTech and Machine Learning
01:30 Challenges in FinTech ML Implementations
02:32 Introducing AWS SageMaker
03:59 Features and Benefits of SageMaker
07:57 Data Preparation with SageMaker
10:03 Model Development and Training
16:19 Model Deployment Options
21:48 Using Go for Machine Learning
26:12 FinTech Use Cases and Success Stories
27:59 Conclusion and Next Steps
Taught by
Conf42