Teoretyczne Podstawy Informatyki

Introduction to Data Science (Wprowadzenie do analityki danych)

Wydział Fizyki, Astronomii i Informatyki Stosowanej,

Uniwersytet Jagielloński w Krakowie

Rok akademicki 2023/2024

Exams:
29.01.2024, godz 9.15 - 10.45, sala A-1-13

23.02.2024, godz 9.15 - 10.45, sala A-2-07

List of questions for exam

Lectures & Assignments:
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Week	Lecture slides	Lab slides	Python scripts with assignments	Datasets	Tutorials
4.10.2023	Introduction Data exploration	Introduction_lab	assignment-1	kc_house_data.csv.zip info on kc_house Example datasets for optional assignments: 1) https://www.mldata.io/dataset-details/school_grades/ 2) https://insights.stackoverflow.com/survey 3) https://stat.gov.pl/ 4) https://www.kaggle.com/nasa/asteroid-impacts 5)https://www.kaggle.com/vik2012kvs/walmart-dataretail-analysis 6)https://www.kaggle.com/dronio/SolarEnergy 7)https://archive.ics.uci.edu/ml/datasets/Heart+failure+clinical+records 8)https://www.kaggle.com/cesartrevisan/scikit-learn-and-gridsearchcv 9)https://www.kaggle.com/osmi/mental-health-in-tech-survey lending-club-data.csv.zip http://snap.stanford.ed/data/amazon/ http://mlr.cs.umass.edu/ml/datasets.html https//data.world/	HowToStartAnaconda Link to GoogleColab DS_cheatsheet_numpy.pdf DS_cheatsheet_matplotlib.pdf DS_cheatsheet_jupyter_notebook.pdf DS_cheatsheet_pandas.pdf Fundamentals of Analysis Box plot
11.10.20223	Regression-Primer Regression-Advanced-I		assignment-2		S.Rashki python-machine-learning-book rashka_ch04.ipynb rashka_ch10.ipynb ElasticNet Regression
18.10.2023	Regression-Advanced-II		assignment-3		numpy tutorial matrix algebra tutorial
25.10.2023	Regression-Advanced-III
8.11.2023	Classification-Primer Classification-Advanced-I		assignment-4	data:amazon_baby.csv.zip	scikit-learn: LogisticRegression
15.11.2023	Odwolane, wyjazd sluzbowy
22.11.2023	Classification-Advanced-II
29.11.2023	Clustering&Retrieval-Primer Clustering&Retrieval-Advanced-I		assignment-5	data:people_wiki.cvs.zip
6.12.2023	Clustering&Retrieval-Advanced-II
13.12.2023	Odwolane, wyjazd sluzbowy				more reading: LDA explained LDA paper
20.12.2023	Recommender-System DeepLearning (on-line, wyjazd sluzbowy)				Recovering Eigenfaces Matrix Factorisation VisualizingAndConvolutionalNN
10.01.2024	Modeling, simulation, Monte Carlo methods.		assignment-6		Computational Modeling Computational Thinking and Data Science
17.01.2024	Statistical Inference		assignment-7
24.01.2024	Multivariate Analyses and Artificial Neural Network				Understanding Deep Learning

Recomended books (.pdf available for download) :
https://hastie.su.domains/ElemStatLearn/
https://hastie.su.domains/ISLP/ISLP_website.pdf
https://probml.github.io/pml-book/
https://www.deeplearningbook.org/

Lectures are based on the materials from Coursera:

C. Guestrin and E. Fox, "Machine Learning Specialisation"
        Foundation: link
        Regression: link
        Classification: link
        Clustering and Retrieval: link

Related interesting material from Coursera
D. Peng, J. Leek and B. Caffo, " Exploratory Data Analysis"
J. Leskovec, A. Rajaraman and J. Ullman, "Mining Massive Datasets"
B. Caffo, R. D. Peng and J. Leek, "Regression Models"

Data Science applications in physics:
B. Nachman,
"Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics"
M. Stoye,
"ML applications in CMS"
ML techniques in HEP, Workshop, Berkeley Laboratory, 11 - 13 December 2018
https://indico.physics.lbl.gov/indico/event/546/

Collection of datasets
http://mlr.cs.umass.edu/ml/datasets.html
http://faculty.marshall.usc.edu/gareth-james/ISL/data.html
http://snap.stanford.edu/data/amazon/

Useful links:
https://turi.com/download/install-graphlab-create-aws-coursera.html
https://turi.com/download/academic.html
https://github.com/turi-code/SFrame

Clustering
http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html
http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html

Boosting
https://turi.com/learn/userguide/supervised-learning/boosted_trees_classifier.html
https://homes.cs.washington.edu/~tqchen/pdf/BoostedTree.pdf
http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html
-----------------
[1] https://class.coursera.org/statistics
[2] http://www.openintro.org/stat/textbook.php
[3] https://class.coursera.org/exdata-006
[4] https://class.coursera.org/mmds
[5] http://www.mmds.org/
[6] http://www.cs.cmu.edu/~awm/tutorials.html

Additional materials
http://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/ADAfaEPoV.pdf
http://statweb.stanford.edu/~tibs/ElemStatLearn/
http://en.wikipedia.org/wiki/Determining_the_number_of_clusters_in_a_data_set
http://www.youtube.com/watch?v=wQhVWUcXM0A

Ostatnia modyfikacja: 30 September 2023

Elzbieta Richter-Was

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