Supervised Learning
Train and evaluate classification and regression models.
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After this skill you can…
- Train decision trees, random forests, and neural nets
- Evaluate with accuracy, F1, AUC
- Avoid overfitting with regularisation
Prerequisites
Watch (10 videos)
Overfitting and Regularization in Deep Learning
→ Train neural networks→ Evaluate model performance
Generative vs Discriminative Models - Explained
→ Implement Naive Bayes and Logistic Regression algorithms→ Analyze the strengths and weaknesses of different classification algorithms
Artificial Intelligence Full Course | AI Tutorial For Beginners | AI Course | #Shorts | #Simplilearn
→ Master supervised learning concepts→ Apply machine learning to real-world problems
Introduction to Artificial Intelligence with Brian Yu - Chapter 4 - Sensing (live, unedited)
→ Apply supervised learning→ Understand ML concepts→ Learn AI basics
How Netflix Handles Large Imbalanced Datasets | Machine Learning Case Study Explained
→ Implement soft impute algorithm to handle missing data→ Evaluate the performance of recommendation systems using RMSE
Machine Learning Full Course Free | Complete Machine Learning Course 2026 | Intellipaat
→ Train supervised learning models→ Evaluate model performance→ Implement regression and classification algorithms
Machine Learning Project for Final Year Students | ML Project Idea @FameWorldEducationalHub
→ Train a supervised learning model→ Evaluate model performance
4. Problem Formulation in AI | Production Systems, Control Strategies & Problem Characteristics
→ Recognize problem characteristics→ Implement machine learning algorithms
2. Artificial Intelligence (AI) Explained | AI Problems, AI Techniques & Real-World Applications
→ Implement supervised learning algorithms→ Solve real-world problems using AI techniques
We just figured out how AI actually works (J-Space)
→ Train AI models→ Evaluate model performance→ Optimize hyperparameters
DeepCamp AI