applied-machine-learning

Week	Topic	Exam
1	Introduction
2	Single variable Linear Regression
3	Multiple variables Linear Regression
4	Workshop I: Introduction to Kaggle
5	Logistic Regression
6	Regularization
7	Evaluation
8	Workshop II
-		Midterm exam (30%) + Kaggle competition (20%)
9	KNN
10	Decision tree
11	Neural network
12	Support Vector Machine (SVM)
13	Clustering: K-Means
14	PCA
15	Modern ML techniques
-		Final exam (30%)
-		Final project (20%)

Reference

Generative VS Discriminative

https://www.analyticsvidhya.com/blog/2021/07/deep-understanding-of-discriminative-and-generative-models-in-machine-learning/

In-class competition

https://www.kaggle.com/c/nida-competition1/submissions

Time series

https://otexts.com/fpp2/MA.html

https://towardsdatascience.com/time-series-decomposition-and-statsmodels-parameters-69e54d035453

Math for ML

https://gwthomas.github.io/docs/math4ml.pdf

Social network

https://sefiks.com/2021/06/06/graph-embeddings-in-neo4j-with-graphsage/?fbclid=IwAR1jduBXBMLeB189WCQyvOx4gvn6pswvJbB0rRQzbB8Nvy_zkpjL5aMhW9g

https://people.idsia.ch/~juergen/

Others

https://medium.com/@kirk.borne/the-importance-of-location-in-real-estate-weather-and-machine-learning-8b12627c5744

Good project

https://github.com/pjwebdev/Basic-Data-Science-Projects

Time series

https://www.bounteous.com/insights/2020/09/15/forecasting-time-series-model-using-python-part-one/

Data integration

Pandas https://pandas.pydata.org/docs/user_guide/10min.html

Join https://www.analyticsvidhya.com/blog/2021/06/join-the-dataframes-like-sql-tables-in-python-using-pandas/

Useful

• https://twitter.com/DataScienceDojo/status/1454585658685657090?t=dOWacKO387XW_9oC9Ig6aA&s=09
• https://twitter.com/ccmccomb/status/1462554716018290695

Toos:

• https://github.com/CalculatedContent/WeightWatcher
• https://github.com/pycaret/pycaret
• https://github.com/automl/auto-sklearn
• https://autokeras.com/

Useful info

1. https://medium.datadriveninvestor.com/significance-of-i-i-d-in-machine-learning-281da0d0cbef

2. https://www.kaggle.com/gloriousc/insurance-forecast-by-using-linear-regression/script

Real case-study in Applied ML

1. Trading bot MyPort

1.1 https://www.myport.pro/?fbclid=IwAR3_aV_K87KZSMw4jDPDFvIUuwVuUV1CL8XGW_TYV56bx3ZTuNrndSKlmb8
1.2

2. Trading Bot BOTUS Will Buy And Sell Stock Based On Trump's Tweets

https://www.npr.org/2017/04/14/523890750/twitter-bot-botus-will-buy-and-sell-stock-based-on-trumps-tweets

3. Process automation at Morgan Stanley

https://www.morganstanley.com/ideas/process-automation

Med

Diagnostic performance of deep learning based voice analysis for diabetes screening

AI in Healthcare An overview and applications in Ophthalmology

4. Research paper

https://www.bc.edu/content/dam/files/schools/cas_sites/cs/pdf/academics/honors/16Lu.pdf

5. Cheat sheet

• ML : https://github.com/ml874/Data-Science-Cheatsheet/blob/master/data-science-cheatsheet.pdf
• Probability : https://static1.squarespace.com/static/54bf3241e4b0f0d81bf7ff36/t/55e9494fe4b011aed10e48e5/1441352015658/probability_cheatsheet.pdf

Machine learning กับ ธนาคาร

https://www.gsbresearch.or.th/wp-content/uploads/2018/06/20IN_hotissue_AI_internet_detail.pdf

Great video lecture

• https://www.youtube.com/watch?v=ngLyX54e1LU&list=PLqnslRFeH2Upcrywf-u2etjdxxkL8nl7E&index=1