-
Notifications
You must be signed in to change notification settings - Fork 3
/
PhD Education3.txt
115 lines (86 loc) · 6.04 KB
/
PhD Education3.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
https://news.efinancialcareers.com/uk-en/285249/machine-learning-and-big-data-j-p-morgan
https://machinelearningmastery.com/how-to-get-started-with-deep-learning-for-time-series-forecasting-7-day-mini-course/
https://machinelearningmastery.com/how-to-develop-convolutional-neural-network-models-for-time-series-forecasting/
https://machinelearningmastery.com/how-to-develop-convolutional-neural-networks-for-multi-step-time-series-forecasting/
https://quantra.quantinsti.com/dashboard
https://www.datacamp.com/profile/elvishlongwane
https://www.quantopian.com/tutorials/getting-started
http://www.wildml.com/
https://www.quantstart.com/articles
http://colah.github.io/posts/2015-08-Understanding-LSTMs/
HANDS ON AI + Python
https://medium.com/@alexrachnog
Machine Learning = Pattern reg
==============================
ML Ccheat Sheet
https://ml-cheatsheet.readthedocs.io/en/latest/loss_functions.html
NB NB NB: http://www.statsoft.com/textbook/time-series-analysis
http://www.statsoft.com/textbook/time-series-analysis
Internet Book: NB NB NB http://neuralnetworksanddeeplearning.com/index.html
TIME SERIES
http://www.seanabu.com/2016/03/22/time-series-seasonal-ARIMA-model-in-python/
MUST DO
https://medium.com/me/list/bookmarks
RESOURCES(Articles + intros)
https://heartbeat.fritz.ai/machine-learning/home
MUST READ - 3 Series(Based on http://www.deeplearningbook.org/, https://github.com/janishar/mit-deep-learning-book-pdf/blob/master/complete-book-pdf/deeplearningbook.pdf, https://www.deeplearningbook.org/front_matter.pdf)
https://towardsdatascience.com/a-gentle-introduction-to-deep-learning-part-1-introduction-43eb199b0b9
https://towardsdatascience.com/a-gentle-introduction-to-deep-learning-part-2-linear-algebra-basics-7139391402c5
https://towardsdatascience.com/a-gentle-introduction-to-deep-learning-part-3-977d0fd1ee5c
Maybe related to the above series- Linear regresision concepts: https://towardsdatascience.com/supervised-learning-basics-of-linear-regression-1cbab48d0eba
READ HYPERPARAMETERS: https://towardsdatascience.com/artificial-intelligence-hyperparameters-48fa29daa516
CLEAR THEORY: https://towardsdatascience.com/intro-to-deep-learning-c025efd92535
https://medium.com/mlreview/a-simple-deep-learning-model-for-stock-price-prediction-using-tensorflow-30505541d877
Creating my neural network: https://towardsdatascience.com/first-neural-network-for-beginners-explained-with-code-4cfd37e06eaf
https://www.statworx.com/ch/blog/deep-learning-teil-2-programmierung/
https://medium.com/thinkgradient/automated-machine-learning-an-overview-5a3595d5c4b5
Stock Market Prediction by Recurrent Neural Network on LSTM Model - Clear code: https://medium.com/@aniruddha.choudhury94/stock-market-prediction-by-recurrent-neural-network-on-lstm-model-56de700bff68
https://medium.com/@TalPerry/deep-learning-the-stock-market-df853d139e02
https://github.com/topics/pattern-recognition?l=python
https://stackoverflow.com/questions/45797452/pattern-recognition-in-datasets-without-visualisation-for-data-analysis
https://www.researchgate.net/post/How_do_I_do_pattern_identification_and_recognition_in_Python
http://www.cs.tut.fi/kurssit/SGN-41007/slides/Lecture1.pdf
http://www.researchpipeline.com/wordpress/2011/02/15/python-data-mining-packages/
Machine Learning and Pattern Recognition for Stocks and Forex
https://www.youtube.com/watch?v=2VVKW5uhZUM&list=PLQVvvaa0QuDe6ZBtkCNWNUbdaBo2vA4RO&index=11&ab_channel=sentdex
Portfolio optimization and back testing
========================================
https://www.pythonforfinance.net/2019/01/
https://www.pythonforfinance.net/2018/12/21/learning-python-my-personal-journey/#more-16051
https://www.pythonforfinance.net/category/trading-strategy-backtest/
https://towardsdatascience.com/efficient-frontier-portfolio-optimisation-in-python-e7844051e7f
http://cycles.technicalanalysis.org.uk/
https://www.mql5.com/en/forum/183790
https://www.pdfpit.com/john/john-ehlers-indicators
http://www.technicalanalysis.org.uk/key.html
https://vdthangmeomeo.files.wordpress.com/2017/08/thomas-bulkowski-encyclopedia-of-chart-patterns-2nd-edition-1034-pages.pdf
http://stockspotter.com/In/Analyzer.aspx?Sym=SPY
Pattern_Recognition_Master_v3(Remastered) and PinbarDetector => https://www.forexfactory.com/showthread.php?t=602203
Kaufman - with filter https://forex-station.com/viewtopic.php?p=1295383411#p1295383411 or https://forex-station.com/viewtopic.php?f=579496&t=8416798&start=2130
Decompiler
http://www.ex4-to-mq4.com/?fjeirkdjfugne84jg94j=appsoluxions%40gmail.com
Pattern Extraction in Stock Market data
http://www.cs.uccs.edu/~jkalita/work/StudentResearch/RajagopalSureshMSProject2016.pdf
Research source
http://alo.mit.edu/research/
Top 6 Tools
https://heartbeat.fritz.ai/top-7-libraries-and-packages-of-the-year-for-data-science-and-ai-python-r-6b7cca2bf000
https://quantra.quantinsti.com/courses
www.datacamp.com
Python-based framework for backtesting trading strategies & analyzing financial markets
https://github.com/constverum/Quantdom
Theory
https://towardsdatascience.com/simply-deep-learning-an-effortless-introduction-45591a1c4abb
extra
http://www.signalprocessingsociety.org/
Tools
https://pymc3.readthedocs.io/en/latest/
https://medium.com/thinkgradient/automated-machine-learning-an-overview-5a3595d5c4b5
-References tsfresh: https://tsfresh.readthedocs.io/en/latest/text/forecasting.html
https://www.automl.org/
https://medium.com/analytics-vidhya/automated-time-series-rstudio-release-avbytes-ml-ai-3e16d6364b58
Prophet: https://www.analyticsvidhya.com/blog/2018/05/generate-accurate-forecasts-facebook-prophet-python-r/ or https://facebook.github.io/prophet/docs/quick_start.html
H2O AutoML vs auto-sklearn: https://www.r-bloggers.com/a-performance-benchmark-of-different-automl-frameworks/
https://www.datasciencecentral.com/profiles/blogs/automated-machine-learning-for-professionals
https://towardsdatascience.com/how-to-beat-automl-hyperparameter-optimisation-with-flair-3b2f5092d9f5
https://towardsdatascience.com/implementing-a-corporate-ai-strategy-a64e641384c8