| English | Chinese |
|---|---|
| ad-hoc, ad hoc (fix/method) | 特设的（修改/方法） |
| training (dataset) | 训练（集） n. |
| evaluation (dataset) | 验证（集） n. |
| testing (dataset) | 测试（集） n. |
| train | 训练 v. |
| evaluate | 验证 v. |
| test | 测试 v. |
| 试 v. | |
See also:
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.
This is a summary of KD-nuggets blogs: here and here. Pictures are modified for my own notes.
Possible framework 1: Hadoop + Spark + Python + scikit.
Possible framework 2: SQL+ Excel + Tableau.
Try NOT use: RapidMiner, KNIME (whatever situation).
Conclusion 1: Big_Data & DL are positively related.
Conclusion 2: Scala is designed/dedicated for Big_Data & DL.