Overview
In this free session with Thomas Nield, you’ll gain a clear understanding of how statistics forms the backbone of machine learning and where the two disciplines overlap and diverge. Designed as a foundation-building session, it will help you connect the dots before diving deeper into more practical, advanced applications in our upcoming paid event.
Topics we’ll cover:
- Statistics and ML - same yet different
- Linear regression, logistic regression, and neural networks
- Verifying models - two schools of thought
Key learnings:
- Understand how statistics and machine learning both share and diverge in their approaches
- Explore the relationship between linear regression, logistic regression, and neural networks
- Learn how statistics plays a critical role in verifying models
End goal:
By the end of the session, you’ll have a solid awareness of how statistics and machine learning share tools but approach problems differently, giving you the foundation needed to advance into more actionable and high-impact applications.
Who should attend:
Budding data science professionals, data analysts, data engineers, and software engineers who want to strengthen their statistical intuition for machine learning.
