cmcrawford4792

cmcrawford4792's Stars

• pmichaillat/hugo-website

  Minimalist Hugo template for academic websites

  Language:HTML151107

• pmichaillat/latex-presentation

  Minimalist LaTeX template for academic presentations

  Language:TeX18551

• jmbh/EmotionTimeSeries

  Data archive of seven open emotion time series from studies using Experience Sampling Methodology

  Language:R101

• marklhc/MCWorkshop

  Materials for the "Advancing Quantitative Science with Monte Carlo Simulation" workshop

  Language:R8

• thomvolker/OptimizationCourse

  Language:HTML1

• talbaram3192/Emotion_Recognition_project

  Language:Jupyter Notebook229

• benjaminfields/CSS_project4_group2

  Language:Jupyter Notebook2

• uo-ec607/lectures

  Lecture notes for EC 607

  Language:HTML1.6k638

• AllenDowney/ThinkBayes2

  Text and code for the second edition of Think Bayes, by Allen Downey.

  Language:Jupyter Notebook1.8k1.5k

• TheAlgorithms/Python

  All Algorithms implemented in Python

  Language:Python196k46.1k

• christophM/interpretable-ml-book

  Book about interpretable machine learning

  Language:Jupyter Notebook4.8k1.1k

• UBC-MDS/public

  Public documents for the Master of Data Science program at the University of British Columbia

  22071

• pymc-devs/pymc-resources

  PyMC educational resources

  Language:Jupyter Notebook2k745

• wesm/pydata-book

  Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

  Language:Jupyter Notebook22.5k15.3k

• jakevdp/PythonDataScienceHandbook

  Python Data Science Handbook: full text in Jupyter Notebooks

  Language:Jupyter Notebook43.6k18k

• data-8/materials-sp21

  Language:Jupyter Notebook23

• dbamman/anlp21

  Data and code to support "Applied Natural Language Processing" (INFO 256, Fall 2021, UC Berkeley)

  Language:Jupyter Notebook5519

• dlab-berkeley/Computational-Social-Science-Training-Program

  This course is a rigorous, year-long introduction to computational social science. We cover topics spanning reproducibility and collaboration, machine learning, natural language processing, and causal inference. This course has a strong applied focus with emphasis placed on doing computational social science.

  Language:Jupyter Notebook22696