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斯坦福机器学习作业(Andrew Ng)

title_image

徒手手工实现算法!!

如何开始:

作业包依赖 Dependencies

This project was coded in Python 3.6

  • numpy
  • matplotlib
  • scipy
  • scikit-learn
  • scikit-image
  • nltk

环境安装 Installation

The fastest and easiest way to install all these dependencies at once is to use Anaconda.

作业:

[Exercise 1]

  • Linear Regression
  • Linear Regression with multiple variables

[Exercise 2]

  • Logistic Regression
  • Logistic Regression with Regularization

[Exercise 3]

  • Multiclass Classification
  • Neural Networks Prediction fuction

[Exercise 4]

  • Neural Networks Learning

[Exercise 5]

  • Regularized Linear Regression
  • Bias vs. Variance

[Exercise 6](

  • Support Vector Machines
  • Spam email Classifier

[Exercise 7]

  • K-means Clustering
  • Principal Component Analysis

[Exercise 8]

  • Anomaly Detection
  • Recommender Systems