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Machine learning online course from Andrew Ng.

MATLAB 11.57% HTML 60.45% Jupyter Notebook 27.98%

machine-learning-andrew-ng's Introduction

machine learning Andrew Ng

Machine learning online course from Andrew Ng.

slides

  • Lecture1 (week1): Introduction
  • Lecture2 (week1): Linear Regression with One Variable
  • Lecture3 (week1): Linear Algebra Review
  • Lecture4 (week2): Linear Regression with Multiple Variables
  • Lecture5 (week2): Octave/Matlab Tutorial
  • Lecture6 (week3): Logistic Regression
  • Lecture7 (week3): Regularization
  • Lecture8 (week4): Neural Networks: Representation
  • Lecture9 (week5): Neural Networks: Learning
  • Lecture10 (week6): Advice for Applying Machine Learning
  • Lecture11 (week6): Machine Learning System Design
  • Lecture12 (week7): Support Vector Machines
  • Lecture13 (week8): Unsupervised Learning
  • Lecture14 (week8): Dimensionality Reduction
  • Lecture15 (week9): Anomaly Detection
  • Lecture16 (week9): Recommender Systems
  • Lecture17 (week10): Large Scale Machine Learning
  • Lecture18 (week11): Application Example: Photo OCR

homework

  • Programming Exercise 1: Linear Regression [python version]
  • Programming Exercise 2: Logistic Regression [python version]
  • Programming Exercise 3: Multi-class Classification and Neural Networks [python version]
  • Programming Exercise 4: Neural Networks Learning [python version]
  • Programming Exercise 5: Regularized Linear Regression and Bias v.s. Variance [python version]
  • Programming Exercise 6: Support Vector Machines [python version]
  • Programming Exercise 7: K-means Clustering and Principal Component Analysis [python version]
  • Programming Exercise 8: Anomaly Detection and Recommender Systems [python version]

videos & PPT

https://pan.baidu.com/s/1n2zg0tW2RA_4HGIgZsuk3w 00yr

additional materials (in Chinese)

https://github.com/fengdu78/Coursera-ML-AndrewNg-Notes

machine-learning-andrew-ng's People

Contributors

qinhanmin2014 avatar

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