Machine Learning Core Concepts
Objective 2.1 · Machine Learning
Supervised vs Unsupervised Learning
Objective 2.1 · Machine Learning
Regression and Classification
Objective 2.2 · Machine Learning
Deep Learning and Neural Networks
Objective 2.3 · Machine Learning
Azure Machine Learning Studio
Objective 2.4 · Machine Learning
Automated ML (AutoML)
Objective 2.4 · Machine Learning
Clustering
Objective 2.2 · Machine Learning
Features, Labels, and Training Data
Objective 2.1 · Machine Learning
Training, Validation, and Test Data Splits
Objective 2.1 · Machine Learning
Overfitting, Underfitting, and Model Complexity
Objective 2.1 · Machine Learning
ML Evaluation Metrics: Accuracy, Precision, Recall
Objective 2.2 · Machine Learning
Confusion Matrix and ROC Curve
Objective 2.2 · Machine Learning
Decision Trees and Random Forests
Objective 2.2 · Machine Learning
Linear vs Logistic Regression
Objective 2.2 · Machine Learning
Anomaly Detection
Objective 2.2 · Machine Learning
Recommendation Systems
Objective 2.2 · Machine Learning
Time Series Forecasting
Objective 2.2 · Machine Learning
Convolutional Neural Networks (CNN)
Objective 2.3 · Machine Learning
RNNs and Transformer Architecture
Objective 2.3 · Machine Learning
Transfer Learning and Pre-Trained Models
Objective 2.3 · Machine Learning
Azure Machine Learning Workspace
Objective 2.4 · Machine Learning
Azure ML Designer: Drag-and-Drop ML
Objective 2.4 · Machine Learning
Azure ML Notebooks and Compute Clusters
Objective 2.4 · Machine Learning
Azure ML Endpoints: Real-Time and Batch
Objective 2.4 · Machine Learning
Responsible AI Dashboard in Azure ML
Objective 2.4 · Machine Learning
No-Code AI Tools: Lobe, Teachable Machine
Objective 2.4 · Machine Learning
MLOps Concepts: Model Registry and Monitoring
Objective 2.4 · Machine Learning
Azure ML Pipelines for Batch Inference
Objective 2.4 · Machine Learning
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