Resources

• Python for Everybody. Very beginners: https://www.py4e.com/lessons

• Intermediate Python Programming Course. A very valuable 6-hour video by Patrick Loeber via freeCodeCamp.org: https://www.youtube.com/watch?v=HGOBQPFzWKo

• Machine Learning by Andrew Ng at Stanford University via Coursera [MOOC]: https://www.coursera.org/learn/machine-learning

• Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow [notebooks]: https://github.com/ageron/handson-ml2

Machine Learning with Graphs (graph representation learning):

• Syllabus: http://cs224w.stanford.edu

• Videos: https://www.youtube.com/playlist?list=PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn

• MIT's introductory course on deep learning, 6.S191: http://introtodeeplearning.com/ Youtube: https://youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI

• DeepMind and the UCL Centre for Artificial Intelligence lecture series [Youtube Playlist]: https://youtube.com/playlist?list=PLqYmG7hTraZCDxZ44o4p3N5Anz3lLRVZF

• Grokking Deep Learning [book]: https://livebook.manning.com/book/grokking-deep-learning/about-this-book/

• Searchable data on Google: https://toolbox.google.com/datasetsearch/search?query=entrepreneurship&docid=5guC6dMaMDd5DoLnAAAAAA%3D%3D

• Labour statistics US https://ilostat.ilo.org/, and its R package https://ilostat.github.io/Rilostat/

• Labour statistics Europe https://ec.europa.eu/eurostat/ and its R package https://cran.r-project.org/web/packages/eurostat/index.html

• WORLD BANK - https://data.worldbank.org/

• GALI - www.galidata.org/entrepreneurs

• Entrepreneurial dynamics panel surveys:

  • I - www.icpsr.umich.edu/web/ICPSR/studies/37203/versions/V1

  • II - www.icpsr.umich.edu/web/ICPSR/studies/37202/versions/V1

• THE COMPARATIVE IMMIGRANT ENTREPRENEURSHP PROJECT (CIEP) - cmd.princeton.edu/publications/data-archives/ciep

• KAUFFMAN FIRM SURVEY - www.kauffman.org/entrepreneurship/reports/...

• INDICATORS OF ENTREPRENEURSHIP - indicators.kauffman.org/data-downloads

• NATIONAL LONGITUDINAL SURVEY of YOUTH (NLSY) - www.bls.gov/nls

• ANNUAL SURVEY OF ENTREPRENEURS (ASE) - www.census.gov/programs-surveys/ase.html

• SURVEY OF BUSINESS OWNERS AND SELF-EMPLOYED PERSONS (SBO) - www.census.gov/programs-surveys/sbo.html

• NZ data:

  • https://maori.figure.nz/

  • https://teic.mbie.govt.nz/

My favourite resources for learning statistics

• Online Course, Improving Your Statistical Inferences, Coursera: https://www.coursera.org/learn/statistical-inferences?fbclid=IwAR1iRvSH5nfs_RhRqV0-udP6pRs5rOehzJL6OjFM9fZKf_Uif4ONfCtutVM

• Statistics in Medicine, Online Self Paced Course, Stanford: https://lagunita.stanford.edu/courses/Medicine/MedStats-SP/SelfPaced/about

• Marin Stats Lectures: https://www.statslectures.com/

• Quant Psych. Very fun stats videos. Check this one out on interactions: https://youtu.be/3CCkeFShB3U

• Passion Driven Statistics: https://passiondrivenstatistics.com/

• Richard McElreath, Statistical Rethinking. YouTube Videos. https://www.youtube.com/channel/UCNJK6_DZvcMqNSzQdEkzvzA/playlists

• Other videos:

  • Power Analysis and Sample Size Decisions https://youtu.be/Lr-i4Ugoc5M

• Learning statistics with R: A tutorial for psychology students and other beginners. (Version 0.6.1). Danielle Navarro https://learningstatisticswithr.com/book/

• Course: swirl. https://swirlstats.com/

• Course: Page Piccinini's ‘R for Publication': https://pagepiccinini.com/r-course/

• Course: Sean Murphy's 'A Psychologist's Guide to R': https://github.com/seanchrismurphy/A-Psychologists-Guide-to-R

• Andy J. Wills' Absolute Beginners’ Guide to R: https://ajwills72.github.io/rminr/

• Glasgow's, Data Skills for Reproducible Science: https://psyteachr.github.io/msc-data-skills/

• Grolemund & Wickham's R for Data Science https://r4ds.had.co.nz/

• Marin Stats Lectures: https://www.statslectures.com/ , videos: https://www.youtube.com/user/marinstatlectures/playlists

• Analysing Longitudinal or Panel Data by Lüdecke et al: https://easystats.github.io/parameters/articles/demean.html

Dictionary approaches:

• Cat Scanner (hosted by Aaron McKenny), open-source: http://catscanner.net/

• Linguistic Inquiry and Word Count (LIWC), https://liwc.wpengine.com/

Sentiment analysis:

• IBM Watson tone analyser tool: https://www.ibm.com/watson/services/tone-analyzer/

• Machine Reading of Hypotheses for Organizational Research Reviews and Pre-trained Models via R Shiny App for Non-Programmers: https://arxiv.org/abs/2106.16102v1

• Active learning for labelling large volumes of articles "ASReview": https://asreview.nl/

Natural language processing notebooks

• "The Super Duper NLP Repo" has 200+ notebooks with awesome materials and datasets for NLP tasks. https://notebooks.quantumstat.com/

• Keep up with the state-of-the-art here: https://paperswithcode.com/area/natural-language-processing