myfirst

我的學習地圖:

Machine Learning:

1. 機器學習基石上下 (Machine Learning Foundations)---Mathematical Foundations 林軒田教授. https://www.coursera.org/learn/ntumlone-mathematicalfoundations/home/welcome
2. Lecture 1 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. http://work.caltech.edu/telecourse.html
3. Machine Learning A-Z™: Hands-On Python & R In Data Science (Udemy). https://www.udemy.com/machinelearning/
4. 資料科學家-輔仁大學 杜逸寧教授(Weka應用). http://www.sharecourse.net/sharecourse/course/content/homepage/1137
5. 大數據的設計思考 - 雲科大 -(Tableau應用). http://www.sharecourse.net/sharecourse/course/content/chapter/1076

Python:

1. Learn Python Fast and Easy Way (Udemy) https://www.udemy.com/learn-python-overnight/learn/v4/overview
2.  精通Python (Book)博客來網路書店 http://www.books.com.tw/products/0010690075

Web design:

1. Django by example(Book). https://www.packtpub.com/web-development/django-example

2. 全端初體驗:(Udemy) https://www.udemy.com/fullstack-starter/learn/v4/content

Crawler

SKLearn 流程圖

開始把學習到的內容作整理，目前已完成:

1. 回歸模型Regression: simple/Multiple/Polynomial linear regression
2. 分類模型Classfication: Logistic regression, SVM, kernel SVM, Naive Bayes
3. 決策樹Decision Tree & Random Froest
4. 分群Clustering: K-Means
5. 關聯法則: Association Rule: Apriori 待續...