Data Science In Action: Session 7 | Mastering Logistic Regression
Details
Join the 7th session of our Data Science in Action series. Master logistic regression, handle imbalanced datasets with SMOTE
Ready to bridge the gap between theory and real-world implementation? Join us for the 7th session of our "Data Science in Action" series as we deep-dive into Logistic Regression—the foundational powerhouse of classification.
Whether you are looking to master the mathematics behind classification or build end-to-end models ready for production, this session is designed to move you from concept to deployment. We don’t just teach the syntax; we teach the strategic logic behind robust, industry-grade models.
Learning Outcomes
By the end of this intensive session, you will be able to:
Master the Fundamentals: Gain a clear understanding of the sigmoid function, log-odds, and how decision boundaries dictate classification.
Build from Scratch: Develop and train a Logistic Regression model from the ground up to understand the underlying mechanics.
Performance Metrics: Go beyond accuracy by evaluating your model with Confusion Matrices, ROC curves, and AUC scores.
Tackle Overfitting: Apply L1 and L2 regularization techniques to ensure your models generalize well to new data.
Handle Real-World Data: Master the art of managing imbalanced datasets using SMOTE and sophisticated class weighting strategies.
Advanced Classification: Implement multi-class classification using One-vs-Rest and Softmax approaches.
End-to-End Pipeline: Learn to build production-ready classification pipelines using scikit-learn.
Deployment: Gain the confidence to deploy a real-world classification model from end to end.
Who Should Attend?
- Data Science enthusiasts looking to strengthen their foundational modeling skills.
- Students and professionals preparing for technical interviews.
- Practitioners who want to understand how to handle imbalanced data and model deployment effectively.
Event Details
Series: Data Science in Action
Topic: Logistic Regression & Classification Mastery
Date: 30th June, 2026
Time: 2:30 Pm CET
Mode: Microsoft Teams
Ready to level up your machine learning toolkit?
Don't just build models—build solutions that work in the real world. We look forward to seeing you there!
Once Registered, Please Save:
Microsoft Teams meeting
Join: https://teams.microsoft.com/meet/334978648675742?p=0NuL28Lw6Ea5I6dfOi
Meeting ID: 334 978 648 675 742
Passcode: J2wk7dJ7