Welcome to Day 13 of WisdomAcademyAI, where we’re classifying data with the magic of Logistic Regression! I’m Anastasia, your super thrilled AI guide, and today we’ll explore Logistic Regression—a powerful ML technique for classification tasks like predicting customer churn. Sophia joins me with a magical demo using Python and scikit-learn to classify churn—it’s spellbinding! Whether you’re new to AI or following along from Days 1–12, this 28-minute lesson will ignite your curiosity. Let’s make AI magic together!
Task of the Day: Build a Logistic Regression model using Python (like in the demo) and share your accuracy in the comments! Let’s see your magical results!
On www.oliverbodemer.eu/dailyaiwizard are the files available to practice the demo.
Subscribe for Daily Lessons: Don’t miss Day 14, where we’ll explore Decision Trees for Classification. Hit the bell to stay updated!
Watch Previous Lessons:
Day 1: What is AI?
Day 2: Types of AI
Day 3: Machine Learning vs. Deep Learning vs. AI
Day 4: How Does Machine Learning Work?
Day 5: Supervised Learning Explained
Day 6: Unsupervised Learning Explained
Day 7: Reinforcement Learning Basics
Day 8: Data in AI: Why It Matters
Day 9: Features and Labels in Machine Learning
Day 10: Training, Testing, and Validation Data
Day 11: Algorithms in Machine Learning (Overview)
Day 12: Linear Regression Basics
#AIForBeginners #LogisticRegression #MachineLearning #WisdomAcademyAI #PythonDemo #ScikitLearnDemo #ClassificationMagic
