Version du 7 novembre 2024 à 05:15

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/
  • 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/
• 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
  • Tanagra by the same author
• MOOC by IVADO on deep learning https://cours.edulib.org/courses/course-v1:IVADO+IA-101+P2018/
• Software
  • Weka

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