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

• 課程：https://www.coursera.org/learn/machine-learning/home

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...