Machine Learning學習日記 — Coursera篇 (Week 0):目錄暨前言


上一篇:學習動機
下一篇:Introduction

Google了一下:Google brain、Coursera共同創辦人、百度首席資料科學家......恩….,Andrew哥,你…我....

(Andrew哥,之後就請多多指教啦,小弟會懷著感恩的心學習的)

1. 資源

之後會根據上課的每個Part做出該章節的筆記,以利於架構的有序

雖然是學習"日"記,但畢竟還有其他外務而無法定期更新。我會盡量一個禮拜更新一次的(掩面)

2. 章節

Week 1

  1. Introduction
  2. Linear Regression with One Variable(上)
  3. Linear Regression with One Variable(下)
  4. Linear Algebra Review(上)
  5. Linear Algebra Review(下)

Week 2

  1. Multivariate Linear Regression(上)
  2. Multivariate Linear Regression(下)
  3. Computing Parameters Analytically
  4. Octave Tutorial

Week 3

  1. Classification and Representation
  2. Logistic Regression Model
  3. Multiclass classification
  4. Regularization

Week 4

  1. Motivations
  2. Neural Networks
  3. Applications

Week 5

  1. Cost Function and BackPropagation
  2. BackPropagation in Practice(上)
  3. BackPropagation in Practice(下)

Week 6

  1. Evaluating a Learning Algorithm
  2. Bias vs. Variance
  3. Building a Spam Classifier
  4. Handling Skewed Data
  5. Using Large Data Sets

Week 7

  1. Large Margin Classification(上)
  2. Large Margin Classification(下)
  3. Kernels(上)
  4. Kernels(下)
  5. SVMs in Practice

to be continued...