D-Lab
- 262 followers
- Social Sciences Building, Berkeley, CA
- http://dlab.berkeley.edu
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Repositories
- MAXQDA-Fundamentals Public
D-Lab's 2 hour introduction to MAXQDA. Learn how to conduct qualitative data analysis using MAXQDA.
dlab-berkeley/MAXQDA-Fundamentals’s past year of commit activity - Python-Fundamentals Public
D-Lab's 6-part, 12-hour introduction to Python. Learn how to create variables, use methods and functions, work with if-statements and for-loops, and do data analysis with Pandas, using Python and Jupyter.
dlab-berkeley/Python-Fundamentals’s past year of commit activity - Python-Deep-Learning Public
D-Lab's 2-hour introduction to deep learning in Python. Learn how to create and train neural networks using Tensorflow and Keras.
dlab-berkeley/Python-Deep-Learning’s past year of commit activity - Python-Data-Wrangling Public
D-Lab's 3-hour workshop diving deep into Pandas. Learn how to manipulate, index, merge, group, and plot data frames using Pandas functions.
dlab-berkeley/Python-Data-Wrangling’s past year of commit activity - Python-Machine-Learning Public
D-Lab's 6 hour introduction to machine learning in Python. Learn how to perform classification, regression, clustering, and do model selection using scikit-learn in Python.
dlab-berkeley/Python-Machine-Learning’s past year of commit activity - Copilot-Fundamentals Public
D-Lab's 2-hour workshop on AI-assisted coding in Visual Studio Code using GitHub Copilot
dlab-berkeley/Copilot-Fundamentals’s past year of commit activity - Python-GPT-Fundamentals Public
D-Lab's 2-hour introduction to Generative Pretrained Transformers (GPT) for beginners. Learn about text encoding, word embeddings, and the transformer architecture upon which GPT is based. Create texts using a GPT model with the Transformers library in Python, and learn about hyperparameters such as temperature.
dlab-berkeley/Python-GPT-Fundamentals’s past year of commit activity - Computational-Social-Science-Training-Program Public
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.
dlab-berkeley/Computational-Social-Science-Training-Program’s past year of commit activity - Python-Data-Visualization Public
D-Lab's 4-hour introduction to data visualization with Python. Learn how to create histograms, bar plots, box plots, scatter plots, compound figures, and more, using matplotlib and seaborn.
dlab-berkeley/Python-Data-Visualization’s past year of commit activity