計劃進修PhD/Research討論區(89) No paper, No PhD?

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五星級肥貓 2019-06-03 21:53:29

ひめたん-伊之助 2019-06-03 22:29:15

明治朱古力 2019-06-03 22:36:55

另外有興趣想留自己Research Info既巴絲, 希望可以搵到同field既巴打傾下計或者睇下有無potential collaboration, 可以係下面個google doc填自己既資料(optional)
https://docs.google.com/spreadsheets/d/1omPI-JkqPDGorbH5_OBOijLib4lwYb9zrFSQ4jGncnI/edit?usp=sharing

如果你想分享下報pg經驗，或者知多啲關於報pg嘅嘢，可以入去呢個google doc：
https://docs.google.com/document/d/1-6RuzKFOdboyqvHGpUcDhZpLz833E2m8jEi3FJfnUCI/edit

有興趣係academic發展，做research既巴絲入黎傾下啦

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明治朱古力 2019-06-03 22:37:45

數統電腦自學資源:

A. Maths:

Linear algebra:
ODE: Nagle, R. K., Saff, E. B., Snider, A. D., & West, B. (1996). Fundamentals of differential equations and boundary value problems. Reading: Addison-Wesley.
PDE:
Numerical analysis:
Optimisation: Boyd, S. & Vandenberghe, L. (2004). Convex Optimization. Cambridge University Press. URL https://www.stanford.edu/~boyd/cvxbook/
Elementary probability: Ross, S. M. (2014). A First Course in Probability (9th edition). Pearson.
Measure-theoretic probability theory: Chung, K. L. (2000). A Course in Probability Theory (2nd edition). Academic Press.
Elementary stochastic processes: Ross, S. M. (2014). Introduction to Probability Models (11th edition). Academic Press.
Stochastic calculus: Øksendal, B. (2003). Stochastic Differential Equations (6th edition). Universitext. Springer, Berlin, Heidelberg.

B. Statistics:

Elementary statistics: Miller, I., Miller, M., & Freund, J. E. (1999). John E. Freund's mathematical statistics. Prentice Hall. (easier)
Hogg, R. V., & Craig, A. T. (1995). Introduction to mathematical statistics.(5"" edition) (pp. 269-278). Upper Saddle River, New Jersey: Prentice Hall. (more difficult)
Linear models: Neter, J., Kutner, M. H., Nachtsheim, C. J., & Wasserman, W. (1996). Applied Linear Statistical Models (Vol. 4). Chicago: Irwin.
Bayesian inference: Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2014). Bayesian Data Analysis (Vol. 2). Boca Raton, FL: CRC press.
Generalized Linear Model: Myers, R. H.,‎ Montgomery, D. C.,‎ Vining G. G.,‎ Robinson T. J. (2010). Generalized Linear Models: with Applications in Engineering and the Sciences (2nd Edition). Wiley.
Multilevel/mixed models: Gelman, A., & Hill, J. (2014). Data analysis using regression and multilevel hierarchical models (Vol. 1). New York, NY, USA: Cambridge University Press.
Multivariate:
Study design: Montgomery, D. C. (2017). Design and analysis of experiments. John wiley & sons.
Time series: Tsay, R. S. (2010). Analysis of Financial Time Series (3rd edition). Wiley.
Categorical data analysis: Agresti, A. (2007). An Introduction to Categorical Data Analysis (2nd Edition), Wiley Series in Probability and Statistics. Wiley.
Bootstrap: Efron, B. & Tibshirani, R. (1994). An Introduction to the Bootstrap. Chapman and Hall/CRC.
Statistical inference: Casella, G. &‎ Berger, R. L. (2001). Statistical Inference (2nd Edition). Duxbury Press.
Statistical learning: Hastie, T.,‎ Tibshirani, R. & Friedman J. (2016). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd Edition), Springer Series in Statistics. Springer.

C. Computer Science:

Basic programming:
Information retrieval:
Computational phylogenetics:
Machine learning: Bishop, C. M. (2011). Pattern Recognition and Machine Learning. Springer.
Deep learning: Goodfellow, I., Bengio, Y. & Courville, A. (2016). Deep Learning. The MIT Press.

明治朱古力 2019-06-03 22:38:10