/machine-learning-Ng

Finished; Machine Learning; Coursera; Stanford; Andrew Ng

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machine-learning-Ng

Machine Learning; Coursera; Stanford; Andrew Ng

Finished.

Certificate

Summary:

  1. Supervised Leaning
  • Linear regression, logistic regression, neural networks, SVMs
  1. Unsupervised Learning
  • K-means, PCA, Anomaly detection
  1. Special applications/special topics
  • Reconmmender systems, large scale machine learning
  1. Advice on building a ML system
  • Bias/variance, regularization; deciding what to work on next: evaluation of learning algorithms, learning curves, error analysis, F1 score, ceiling analysis

Weekly summary:

W1: Linear regression

W2: Linear regression with multiple variables

W3: Logistic regression; Regularization

W4/5: Neural Networks; FF; BP;

W6: Validation; Learning curve; regularizaiton with bias and variance; Error metrics(F1 score; precision; recall; accuracy)

W7: SVM

W8: unsupervised, Clustering and PCA

W9: Anomaly Detection; Recommerder systems

W10: Large scale ML: Stochastic gradient descent; Online learning

W11: photo OCR; artificial data; Ceiling analysis


Certificate