Awesome

Machine Learning ~ Stanford

📖 Overview

• Week 1
• Week 2
• Week 3
• Week 4
• Week 5
• Week 6
• Week 7
• Week 8
• Week 9
• Week 10
• Week 11
• Certificate

Week 1

Quizzes

• Introduction
• Linear Regression With One Variable
• Linear Algebra

Week 2

Quizzes

• Linear Regression With Multiple Variables
• Octave/Matlab Tutorial

Programming Exercises

• Questions and Explanation
• Exercise 1
  • Warm Up Exercise
  • Compute Cost for One Variable
  • Compute Cost For Multiple Variables
  • Gradient Descent For One Variable
  • Gradient Descent For Multiple Variables

Week 3

Quizzes

• Logistic Regression
• Regularization

Programming Exercises

• Questions
• Exercise 2
  • Sigmoid Function
  • Logistic Regression Cost
  • Logistic Regression Gradient
  • Regularized Logistic Regression Cost
  • Regularized Logistic Regression Gradient
  • Predict

Week 4

Quizzes

• Neural Networks: Representation

Programming Exercises

• Questions and Explanations
• Exercise 3
  • Logistic Regression Cost Function
  • One vs. All Multi Class Classifier
  • Predict one vs. all Multi Class Classifier
  • Neural Network Prediction Function

Week 5

Quizzes

• Neural Networks: Learning

Programming Exercises

• Questions and Explanations
• Exercise 4
  • Feedforward and Cost Function
  • Regularized Cost Function
  • Compute Gradient of Sigmoid Function
  • Randomly Initialize Weights
  • Neural Network Gradient (Backpropagation)
  • Neural Network Cost Function
  • Regularized Gradient

Week 6

Quizzes

• Advice for Applied Machine Learning
• Machine Learning System Design Quiz

Programming Exercises

• Questions and Explanations
• Exercise 5
  • Regularized Linear Regression Cost Function
  • Generate Learning Curve
  • Maps Data into Polynomial Feature Space
  • Generates a Cross Validation Curve

Week 7

Quizzes

• Support Vector Machines (SVM)

Programming Exercises

• Questions and Explanations
• Exercise 6: Support Vector Machines
  • Gaussian Kernel for SVM
  • Parameters to Use for Dataset 3
  • Email Preprocessing
  • Feature Extraction From Email

Week 8

Quizzes

• Unsupervised Learning
• Principal Component Analysis

Programming Exercises

• Exercise 7: Questions and Explanations
• K Means Clustering and PCA(Principal Component Analysis)
  • Perform PCA(Principal Component Analysis)
  • Project a Dataset into lower dimensional space
  • Recover the Original Data from the Projection
  • Find Closest Centroids Using K-Means
  • Compute Centroid Means
  • Initialize K means for Centroids

Week 9

Quizzes

• Anomaly Detection
• Reccomender Systems

Programming Exercises

• Exercise 8: Questions and Explanations
• Anomaly Detection and Reccomender Systems
  • Estimate Gaussian Parameters
  • Find Threshold for Anomaly Detection
  • Cost Function for Collaborative Filterinf

Week 10

Quizzes

• Large Scale Machine Learning

Week 11

Quizzes

• Application: Photo OCR

🎓 Certificate