Data Science Resources : Différence entre versions
De Transport
(→Statistics) |
|||
| (20 révisions intermédiaires par le même utilisateur non affichées) | |||
| Ligne 8 : | Ligne 8 : | ||
** [https://github.com/jupyter/jupyter/wiki Gallery of Jupyter Notebooks on programming, data science, etc.] | ** [https://github.com/jupyter/jupyter/wiki Gallery of Jupyter Notebooks on programming, data science, etc.] | ||
* Examples and tutorials (Jupyter notebooks) for the transportation data management course CIV8760 (in French) https://github.com/nsaunier/CIV8760/ | * 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 Management= |
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
* [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 [[OpenScience|open science ou science ouverte]], incluant les politiques de gestion des données de recherche | ||
| + | |||
| + | =Numerical Methods= | ||
| + | * Python Programming And Numerical Methods: A Guide For Engineers And Scientists¶ https://pythonnumericalmethods.studentorg.berkeley.edu/notebooks/Index.html | ||
| + | |||
| + | =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: [https://oli.cmu.edu/courses/probability-statistics-open-free/ Probability & Statistics] [https://oli.cmu.edu/courses/statistical-reasoning-copy/ 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) | ||
| + | ** [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= | ||
| − | * | + | * 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 | ** 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) | ||
* [http://profs.polymtl.ca/jagoulet/Site/Goulet_web_page_BOOK.html Probabilistic Machine Learning for Civil Engineers, James Goulet] | * [http://profs.polymtl.ca/jagoulet/Site/Goulet_web_page_BOOK.html Probabilistic Machine Learning for Civil Engineers, James Goulet] | ||
* [https://www.microsoft.com/en-us/research/publication/fourth-paradigm-data-intensive-scientific-discovery/ Hey, T. Tansley, S. & Tolle, K. (Eds.) The Fourth Paradigm: Data-Intensive Scientific Discovery Microsoft Research, 2009] | * [https://www.microsoft.com/en-us/research/publication/fourth-paradigm-data-intensive-scientific-discovery/ Hey, T. Tansley, S. & Tolle, K. (Eds.) The Fourth Paradigm: Data-Intensive Scientific Discovery Microsoft Research, 2009] | ||
* [http://www.kdnuggets.com/ Site KDnuggets] | * [http://www.kdnuggets.com/ Site KDnuggets] | ||
* (French) reference book: Cornuéjols, A.; Miclet, L. & Kodratoff, Y. Apprentissage Artificiel Eyrolles, 2002 | * (French) reference book: Cornuéjols, A.; Miclet, L. & Kodratoff, Y. Apprentissage Artificiel Eyrolles, 2002 | ||
| − | * (French) [ | + | * (French) [https://cours-machine-learning.blogspot.com/ Notes pour les cours de data mining de Ricco Rakotomalala] |
| − | ** [ | + | ** [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= | ||
* Tufte, E. R. The Visual Display of Quantitative Information Graphics Press, 1983 | * Tufte, E. R. The Visual Display of Quantitative Information Graphics Press, 1983 | ||
* Blog: [https://flowingdata.com/ Flowing data], [https://www.reddit.com/r/dataisbeautiful/ Data Is Beautiful (Reddit)] | * Blog: [https://flowingdata.com/ Flowing data], [https://www.reddit.com/r/dataisbeautiful/ Data Is Beautiful (Reddit)] | ||
| + | * https://datavizcatalogue.com | ||
* Articles: Wikipedia [https://en.wikipedia.org/wiki/Diagram diagrams] and [https://en.wikipedia.org/wiki/Chart Charts], [http://queue.acm.org/detail.cfm?id=1805128 ACM paper], [https://www.economist.com/node/15557455 The Economist] | * Articles: Wikipedia [https://en.wikipedia.org/wiki/Diagram diagrams] and [https://en.wikipedia.org/wiki/Chart Charts], [http://queue.acm.org/detail.cfm?id=1805128 ACM paper], [https://www.economist.com/node/15557455 The Economist] | ||
* Labs: | * Labs: | ||
| Ligne 54 : | Ligne 77 : | ||
=Spatial Data= | =Spatial Data= | ||
* Introduction to Geospatial Concepts https://datacarpentry.org/organization-geospatial/ | * Introduction to Geospatial Concepts https://datacarpentry.org/organization-geospatial/ | ||
| − | * QGIS documentation: [https://docs.qgis.org/ | + | * QGIS documentation: [https://docs.qgis.org/latest/fr/docs/index.html français], [https://docs.qgis.org/latest/en/docs/index.html english] |
** A Gentle Introduction to GIS https://docs.qgis.org/latest/en/docs/gentle_gis_introduction/index.html | ** A Gentle Introduction to GIS https://docs.qgis.org/latest/en/docs/gentle_gis_introduction/index.html | ||
** QGIS how-to: [https://www.qgistutorials.com/en/docs/3/creating_heatmaps.html heatmaps], [https://www.giscourse.com/how-to-add-openstreetmap-basemaps-in-qgis-3-0/|add OSM layer] | ** QGIS how-to: [https://www.qgistutorials.com/en/docs/3/creating_heatmaps.html heatmaps], [https://www.giscourse.com/how-to-add-openstreetmap-basemaps-in-qgis-3-0/|add OSM layer] | ||
* SpatiaLite cookbook http://www.gaia-gis.it/gaia-sins/spatialite-cookbook-5/index.html | * SpatiaLite cookbook http://www.gaia-gis.it/gaia-sins/spatialite-cookbook-5/index.html | ||
| + | * Introduction to Python for Geographic Data Analysis https://python-gis-book.readthedocs.io | ||
| + | * Introduction to GIS Programming https://geog-312.gishub.org | ||
* (French) books from EPFL: Systèmes d'Information Géographique [https://www.researchgate.net/publication/320979981_Systemes_d%27Information_Geographique_1 Partie 1] et [https://www.researchgate.net/publication/320980079_Systemes_d%27Information_Geographique_2 Partie 2] | * (French) books from EPFL: Systèmes d'Information Géographique [https://www.researchgate.net/publication/320979981_Systemes_d%27Information_Geographique_1 Partie 1] et [https://www.researchgate.net/publication/320980079_Systemes_d%27Information_Geographique_2 Partie 2] | ||
* (French) resources, including online courses in https://claroline-connect.univ-st-etienne.fr/web/app.php/resource/open/icap_wiki/224152#/ | * (French) resources, including online courses in https://claroline-connect.univ-st-etienne.fr/web/app.php/resource/open/icap_wiki/224152#/ | ||
=Spatial Analysis= | =Spatial Analysis= | ||
| − | * [https://paezha.github.io/ | + | * [https://ipeagit.github.io/intro_access_book/ Introduction to urban accessibility, a practical guide with R] |
| + | * [https://paezha.github.io/spatial-analysis-r/ An Introduction to Spatial Data Analysis and Statistics: A Course in R], Prof. Antonio Paez | ||
* [https://mgimond.github.io/Spatial/index.html Intro to GIS and Spatial Analysis] | * [https://mgimond.github.io/Spatial/index.html Intro to GIS and Spatial Analysis] | ||
* [https://pysal.org Python Spatial Analysis Library (PySAL)] | * [https://pysal.org Python Spatial Analysis Library (PySAL)] | ||
* [https://geodacenter.github.io/documentation.html Documentation de GeoDa] | * [https://geodacenter.github.io/documentation.html Documentation de GeoDa] | ||
* [https://www.spatialanalysisonline.com/ Geospatial Analysis - A comprehensive guide] | * [https://www.spatialanalysisonline.com/ Geospatial Analysis - A comprehensive guide] | ||
| − | + | * [https://spacetimewithr.org Spatio-Temporal Statistics with R] | |
| − | + | ||
| − | * | + | |
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
Version actuelle en date du 23 janvier 2025 à 11:53
Sommaire
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
Numerical Methods
- Python Programming And Numerical Methods: A Guide For Engineers And Scientists¶ https://pythonnumericalmethods.studentorg.berkeley.edu/notebooks/Index.html
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)
- https://datavizcatalogue.com
- 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
- Introduction to Python for Geographic Data Analysis https://python-gis-book.readthedocs.io
- Introduction to GIS Programming https://geog-312.gishub.org
- (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
