Book

Fundamental/Essential Mathmatic Foundation Books & Courses

2021-04-15. Category & Tags: Mathmatic, Book

See also:

Note: The following books are more introductory than professional, but usually enough for most engineers.

Linear Algebra #

  • Sheldon Axler 《Linear Algebra Done Right / 线性代数应该这样学》(以线性变换为中心) [豆瓣 8.8,184 人],图灵社区出品,人民邮电出版社; supplementary videos (English subtitle) on Youtube and Bilibili; slides; Errata. 适合于上课后听不懂的二次自学。
    image
  • 麻省理工 Gilbert Strang “线性代数 MIT 18.06”（网易公开课有翻译） & 教材 《Introduction to Linear Algebra 线性代数》 [第五版 豆瓣 9.5，71 人] 清华大学出版社。 Videos (中英双字幕) on Bilibili & Youtube with Newly added content in 2020。 Strang 教授另有一本《Linear Algebra and Its Applications》，内容差不多。

  • J. Ström, K. Åström 和 T. Akenine-Möller 的《沉浸式线性代数》教程（《Immersive Linear Algebra》）
    大量交互动画演示: 在线交互 ImmersiveMath.com
  • David C. Lay 的《线性代数及其应用》
  • 纯中文： 蓝以中《高等代数简明教程》; 丘维声《简明线性代数》。
  • 视频： 3B1B 线性代数的本质 - 系列合集 16p, 3h

Probability & Statistics #

Calculus #

  • 普林斯顿《The Calculus Lifesaver 微积分读本》 [豆瓣 9.6，629 人] 图灵教育出品, 人民邮电出版社. 没啥可说的，还有 videos on Bilibili (English subtile)，还有《图解普林斯顿微积分读本》。
  • 芬尼 / 韦尔 / 焦尔当诺《托马斯微积分》：直观易读，强调建模应用和技巧训练，重要的是不失数学上的完整性，工科使用应该相当不错。书非常厚, 介绍非常详细。PEARSON Education, 高等教育出版社, 豆瓣 9.4（631 人）
  • James Stewart 《Calculus》 从最简单的开始教。 image (pic: 8th Edition)

Refs #

weixin
CNblogs 数学入门到进阶, (bak)
zhihu
csdn

...

Learning Machine Learning, ML Books & Codes

2018-07-07. Category & Tags: Machine Learning, Artificial Intelligence, Book

See also:

Favoured #

  • DSML (Kroese, Botev et.al. - Chapman Press 2019) Data Science and Machine Learning: Mathematical and Statistical Methods. With public datasets, code and pdf online.

  • NNDL (Michael Nielsen 2016 邱锡鹏（译） 2020.06) Keywords: CNN, RNN, Attention, Gaussian Mix., RBM, DBN, GAN, RL, TF, PyTorch: equation, pseudocode, exercise … 公开了所有代码等内容的（中文）电子书。 PDF, PPT, code, exercise & solution, etc.

  • MLAPP (Kevin Murphy), Machine Learning - A Probablistic Perspective, is more comprehensive, insightful and interesting, and contains more “real” examples/problems. However, the presents are kinda out of order, which can be difficult to follow for a first book.

    ...

Recommender System

2018-01-20. Category & Tags: Recommender System, Recommendation System, Literature, Book, Text, News

This is a detailed reproduction of ref.

Sunny Summary #

3 steps:

  1. preprocessing.py preprocessing to extract: author, average sentence length, average word length, punctuation profile, sentiment scores, part-of-speech profiles/tags (only in code, not taken into the csv).
  2. TFIDF.py content-wise k-means clustering (on TFIDF scores) to get: 3 levels/degrees of clustering/classification results.
  3. knn.py knn search on the results of step 1 and 2 to get: recommendations (k=15 by default).

Preprocessing # 

pip2 install nltk
pip2 install twython  # optional ? got warning, not error.
git clone https://github.com/SunnyBingoMe/gutenberg.git
cd gutenberg/data

Download the books txt data (e.g. the 404M 3k data on Google Drive) and unzip. Then set this folder as the txt_path in preprocessing.py. WARN: do rename 's/:/-/g' *; rename 's/,/\./g' *; rename "s/\"/'/g" *; in the txt files folder. The : char in the filenames will cause problems for spark TFIDF path system. The , may introduce issues for csv files as well as " occuring together with ' in the same files.

...