Learn from Industry Leaders about:

• Supervised vs. Unsupervised Learning: Explore the two paradigms of ML and how they are used to solve different types of problems.
• Data Management and Quality: Learn best practices for handling ML datasets while ensuring data integrity and quality
• Real-World Applications: Discover ML applications across industries from recommender systems to fraud detection
• Challenges and Considerations: Gain insights into key challenges like data bias, explainability, and ethical considerations.