Teoretyczne Podstawy Informatyki

Introduction to Data Science (Wprowadzenie do analityki danych)

Wydział Fizyki, Astronomii i Informatyki Stosowanej,

Uniwersytet Jagielloński w Krakowie

Rok akademicki 2017/2018

Konsultacje: wtorek, godz. 14:00 - 15:00; pokój 2-D-11.

Lectures & Assignments:
-----------------------------------------------------
based on course
C. Guestrin and E. Fox, "Machine Learning Specialisation"

31.10.2017	Introduction Regression-Primer	Primer: assignments snippet data: kc_house_data.csv.zip info on kc_house dataset
7.11.2017	Regression-Advanced Regression-Recap	Advanced: simple-regression-assignment.ipynb.zip multiple-regression-assignment-2.ipynb.zip polynomial-regression-assignment.ipynb.zip ridge-regression-assignment-1.ipynb.zip Overfitting_Demo_Ridge_Lasso.ipynb.zip lasso-assignment-1.ipynb.zip lasso-assignment-2.ipynb.zip local-regression-assignment.ipynb.zip data: kc_house_data.csv.zip info on kc_house dataset
14.11.2017	Classification-Primer	Primer: assignments AnalyzingProductSentiment.ipynb.gz data: amazon_baby.csv.zip
21.11.2017	Classification-Advanced Classification-Recap Classification-Bonus	Advanced: linear-classifier-assignment.ipynb.zip linear-classifier-learning-assignment.ipynb.zip decision-tree-assignment-1.ipynb.zip decision-tree-assignment-2.ipynb.zip decision-tree-practical-assignment.zip boosting-assignment-1.ipynb.zip boosting-assignment-2.ipynb.zip data: amazon_baby.csv.zip dictionary: important_words.json.zip data: lendig-club-data.cvs.zip info on LendingClub dataset
28.11.2017	Clustering-Primer	Primer: assignment: 0_nearest-neighbors-features-and-metrics.ipynb.zip data: people_wiki.cvs.zip example: DocumentRetrieval.ipynb.gz
5.12.2017	Clustering-Advanced Clustering-Recap Clustering-Bonus	Advanced: 1_nearest-neighbors-lsh-implementation.ipynb.zip 2_kmeans-with-text-data.ipynb.zip 3_em-for-gmm.ipynb.zip 4_em-with-text-data.ipynb.zip 5_lda.ipynb.zip 6_hierarchical_clustering.ipynb.zip data & helpers people_wiki.cvs.zip people_wiki_map_index_to_word.json.zip people_wiki_word_count.npz.zip people_wiki_tf_idf.npz.zip kmeans-arrays.npz.zip images.sf.zip chosen_images.png em_utilities.py.zip topic_models.zip
12.12.2017	Lecture&Assignments by Piotr Bialas
19.12.2017	Recommender-Primer DeepLearning-Primer	Primer: SongRecommender.zip Advanced: DeepLearningForClassification.zip

Lectures are based on the materials from Coursera:

Dr. Mine Çetinkaya-Rundel "Data Analysis and Statistical Inference"
D. Peng, J. Leek and B. Caffo, " Exploratory Data Analysis"
J. Leskovec, A. Rajaraman and J. Ullman, "Mining Massive Datasets"
C. Guestrin and E. Fox, "Machine Learning Specialisation"
        Foundation: link
        Regression: link
        Classification: link
        Clustering and Retrieval: link
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/

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

Link to lectures given in 2014
http://th-www.if.uj.edu.pl/~erichter/dydaktyka/Dydaktyka2014/AiSAD-2014/index.html

Ostatnia modyfikacja: 21 listopad 2017

Elzbieta Richter-Was

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