ashoknp-git/machine_learning-1

Machine Learning - Coursera.org

Machine Learning - Coursera.org

• Linear Regression
• Logistic Regression
• Multi-class Classification and Neural Networks
• Neural Network Learning
• Regularized Linear Regression and Bias/Variance
• Support Vector Machines
• K-Means Clustering and PCA
• Anomaly Detection and Recommender Systems

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IV. Linear Regression with Multiple Variables (Week 2)

Linear Regression

• Warm up exercise
• Compute cost for one variable
• Gradient descent for one variable
• Feature normalization (optional)
• Compute Cost for Multiple Variables (optional)
• Gradient Descent for Multiple Variables (optional)
• Normal Equations (optional)

VII. Regularization (Week 3)

Logistic Regression

• Sigmoid Function
• Compute cost for logistic regression
• Gradient for logistic regression
• Predict Function
• Compute cost for regularized LR
• Gradient for regularized LR

VIII. Neural Networks: Representation (Week 4)

Multi-class Classification and Neural Networks

• Regularied Logistic Regression
• One-vs-all classifier training
• One-vs-all classifier prediction
• Neural Network Prediction Function

IX. Neural Networks: Learning (Week 5)

Neural Network Learning

• Feedforward and Cost Function
• Regularized Cost Function
• Sigmoid gradient
• Neural Net Gradient Function (Backpropagation)
• Regularized Gradient

X. Advice for Applying Machine Learning (Week 6)

Regularized Linear Regression and Bias/Variance

• Regularized Linear Regression Cost Function
• Regularized Linear Regression Gradient
• Learning Curve
• Polynomial Feature Mapping
• Cross Validation Curve

XII. Support Vector Machines (Week 7)

Support Vector Machines

• Gaussian Kernel
• Parameters (C, sigma) for Dataset 3
• Email Preprocessing
• Email Feature Extraction

XIV. Dimensionality Reduction (Week 8)

K-Means Clustering and PCA

• Find Closest Centroids
• Compute Centroid Means
• PCA
• Project Data
• Recover Data

XVI. Recommender Systems (Week 9)

Anomaly Detection and Recommender Systems

• Estimate Gaussian Parameters
• Select Threshold
• PCA
• Collaborative Filtering Cost
• Collaborative Filtering Gradient
• Regularized Cost
• Gradient with regularization