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* [http://www.datacarpentry.org/lessons/ Data carpentry] | * [http://www.datacarpentry.org/lessons/ Data carpentry] | ||
* A Quick Guide to Organizing Computational Biology Projects https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000424 | * A Quick Guide to Organizing Computational Biology Projects https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000424 | ||
* Données de recherche https://guides.biblio.polymtl.ca/donneesrecherche | * Données de recherche https://guides.biblio.polymtl.ca/donneesrecherche [[OpenScience|open science ou science ouverte]], incluant les politiques de gestion des données de recherche | ||
=Statistics= | =Statistics= | ||
* Statistical Thinking for the 21st Century https://statsthinking21.org/ | * Statistical Thinking for the 21st Century https://statsthinking21.org/ | ||
* Learning Statistics with R | * Learning Statistics with R https://learningstatisticswithr.com/ | ||
* Answering questions with data https://crumplab.com/statistics/ | * Answering questions with data https://crumplab.com/statistics/ | ||
* Carnegie Mellon University free online courses: [https://oli.cmu.edu/courses/probability-statistics-open-free/ Probability & Statistics] [https://oli.cmu.edu/courses/statistical-reasoning-copy/ Statistical Reasoning] | * Carnegie Mellon University free online courses: [https://oli.cmu.edu/courses/probability-statistics-open-free/ Probability & Statistics] [https://oli.cmu.edu/courses/statistical-reasoning-copy/ Statistical Reasoning] | ||
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** Cours du master économétrie et statistique appliquée de l'Université d’Orléans https://www.univ-orleans.fr/deg/masters/ESA/CH/churlin_E.htm#_Universit%C3%A9_d%27Orl%C3%A9ans,_Master_Econom | ** Cours du master économétrie et statistique appliquée de l'Université d’Orléans https://www.univ-orleans.fr/deg/masters/ESA/CH/churlin_E.htm#_Universit%C3%A9_d%27Orl%C3%A9ans,_Master_Econom | ||
** Explication et interprétation des modèles de choix discrets https://mate-shs.cnrs.fr/actions/tutomate/tuto35-regression-logistique-deauvieau/ | ** Explication et interprétation des modèles de choix discrets https://mate-shs.cnrs.fr/actions/tutomate/tuto35-regression-logistique-deauvieau/ | ||
* Software | |||
** R, Python (scipy, statsmodels) | |||
** [http://gretl.sourceforge.net/ Gretl (econometrics)] | |||
=Artificial Intelligence= | |||
* CS188 Intro to AI http://ai.berkeley.edu | |||
* Finnish MOOC https://buildingai.elementsofai.com/ | |||
=Machine Learning= | =Machine Learning= | ||
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** [https://tanagra-machine-learning.blogspot.com Tanagra by the same author] | ** [https://tanagra-machine-learning.blogspot.com Tanagra by the same author] | ||
* MOOC by IVADO on deep learning https://cours.edulib.org/courses/course-v1:IVADO+IA-101+P2018/ | * MOOC by IVADO on deep learning https://cours.edulib.org/courses/course-v1:IVADO+IA-101+P2018/ | ||
* Software | * Software | ||
** [http://www.cs.waikato.ac.nz/ml/weka/ Weka] | ** [http://www.cs.waikato.ac.nz/ml/weka/ Weka] | ||
=Data Visualization= | =Data Visualization= | ||
Version du 23 février 2024 à 17:06
General Books
- Free books on data science http://www.learndatasci.com/free-data-science-books
- Many online books on various data science topics on https://bookdown.org/
Code
- Data science using Python https://github.com/jakevdp/PythonDataScienceHandbook (see Programming resources for Python and other languages)
- Python data science handbook https://jakevdp.github.io/PythonDataScienceHandbook/
- Examples and tutorials (Jupyter notebooks) for the transportation data management course CIV8760 (in French) https://github.com/nsaunier/CIV8760/
- PolyIT GitHub https://github.com/nsaunier/TransportDataEngineering
Data Management
- Data carpentry
- A Quick Guide to Organizing Computational Biology Projects https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000424
- Données de recherche https://guides.biblio.polymtl.ca/donneesrecherche open science ou science ouverte, incluant les politiques de gestion des données de recherche
Statistics
- Statistical Thinking for the 21st Century https://statsthinking21.org/
- Learning Statistics with R https://learningstatisticswithr.com/
- Answering questions with data https://crumplab.com/statistics/
- Carnegie Mellon University free online courses: Probability & Statistics Statistical Reasoning
- Scientific Approaches to Transportation Research http://onlinepubs.trb.org/Onlinepubs/nchrp/cd-22/start.htm
- Understanding and Communicating Multimodal Transportation Data http://web.cecs.pdx.edu/~monserec/t.data/
- (French) resources
- Cours MTH2302C: Probabilités et statistique, Denis Marcotte http://cours.polymtl.ca/geo/marcotte/mth2302c.html
- Notes et ebooks de Ricco Rakotomalala https://cours-machine-learning.blogspot.com/
- Cours du master économétrie et statistique appliquée de l'Université d’Orléans https://www.univ-orleans.fr/deg/masters/ESA/CH/churlin_E.htm#_Universit%C3%A9_d%27Orl%C3%A9ans,_Master_Econom
- Explication et interprétation des modèles de choix discrets https://mate-shs.cnrs.fr/actions/tutomate/tuto35-regression-logistique-deauvieau/
- Software
- R, Python (scipy, statsmodels)
- Gretl (econometrics)
Artificial Intelligence
- CS188 Intro to AI http://ai.berkeley.edu
- Finnish MOOC https://buildingai.elementsofai.com/
Machine Learning
- List of machine learning books http://matpalm.com/blog/cool_machine_learning_books/
- Pattern Recognition and Machine Learning by Christopher Bishop free at https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
- Neural Networks: Zero to Hero https://karpathy.ai/zero-to-hero.html https://github.com/karpathy/nn-zero-to-hero (NanoGPT https://github.com/karpathy/nanoGPT)
- Probabilistic Machine Learning for Civil Engineers, James Goulet
- Hey, T. Tansley, S. & Tolle, K. (Eds.) The Fourth Paradigm: Data-Intensive Scientific Discovery Microsoft Research, 2009
- Site KDnuggets
- (French) reference book: Cornuéjols, A.; Miclet, L. & Kodratoff, Y. Apprentissage Artificiel Eyrolles, 2002
- (French) Notes pour les cours de data mining de Ricco Rakotomalala
- MOOC by IVADO on deep learning https://cours.edulib.org/courses/course-v1:IVADO+IA-101+P2018/
- Software
Data Visualization
- Tufte, E. R. The Visual Display of Quantitative Information Graphics Press, 1983
- Blog: Flowing data, Data Is Beautiful (Reddit)
- Articles: Wikipedia diagrams and Charts, ACM paper, The Economist
- Labs:
- Human-Computer Interaction Lab and Center for Advanced Transportation Technology Laboratory, University of Maryland
- TRB 5th, 6th, 7th, 8th and 9th International Visualization in Transportation Symposium and Workshop
- Professors Thomas Hurtut (Polytechnique), Éric Lecolinet (Télécom ParisTech)
- Courses
- Data Visualization (CS448b), Stanford
- CS117, Hanspeter Pfister, Harvard
- Videos: The Art of Data Visualization | PBS Digital Studios, Harvard i-lab | Data Visualization for Non-Programmers, Mike Bostock (D3js) - Keynote, Designing Data Visualizations with Noah Iliinsky
- Libraries / tools
- Python: matplotlib, seaborn
- R: ggplot2
- Javascript: D3.js
- Old: gnuplot
Time Series
- Forecasting: Principles and Practice (2nd ed) https://otexts.com/fpp2/
Spatial Data
- Introduction to Geospatial Concepts https://datacarpentry.org/organization-geospatial/
- QGIS documentation: français, english
- A Gentle Introduction to GIS https://docs.qgis.org/latest/en/docs/gentle_gis_introduction/index.html
- QGIS how-to: heatmaps, OSM layer
- SpatiaLite cookbook http://www.gaia-gis.it/gaia-sins/spatialite-cookbook-5/index.html
- (French) books from EPFL: Systèmes d'Information Géographique Partie 1 et Partie 2
- (French) resources, including online courses in https://claroline-connect.univ-st-etienne.fr/web/app.php/resource/open/icap_wiki/224152#/
Spatial Analysis
- Introduction to urban accessibility, a practical guide with R
- An Introduction to Spatial Data Analysis and Statistics: A Course in R, Prof. Antonio Paez
- Intro to GIS and Spatial Analysis
- Python Spatial Analysis Library (PySAL)
- Documentation de GeoDa
- Geospatial Analysis - A comprehensive guide
- Spatio-Temporal Statistics with R
