46 lines
2.5 KiB
Plaintext
46 lines
2.5 KiB
Plaintext
# DMML notebook environment
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#
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# Python 3.11, 3.12 or 3.13. (3.10 is too old: pandas, numpy and scikit-learn
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# all require >=3.11 at these versions.)
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#
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# Install with:
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# python -m pip install -r requirements.txt
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#
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# Versions are PINNED, not floors. This is deliberate for a taught course:
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# everyone gets the same environment, the Gradescope autograder matches your
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# laptop, and a notebook that worked in September still works in December.
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# If you need to move a pin, change it here so the whole class moves together.
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#
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# For GPU PyTorch, install torch/torchvision from the official PyTorch selector
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# for your CUDA version first, then run this file.
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# Jupyter
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jupyterlab==4.5.6
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notebook==7.5.5
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ipykernel==7.2.0
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ipywidgets==8.1.8
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# Core scientific Python
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numpy==2.4.2
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pandas==3.0.2
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matplotlib==3.10.8
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seaborn==0.13.2
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# Classical machine learning and statistics
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scikit-learn==1.8.0
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statsmodels==0.14.6
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shap==0.51.0
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# Neural networks and computer vision
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torch==2.12.0
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torchvision==0.27.0
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# HuggingFace datasets and transformers
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datasets==4.8.5
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transformers==5.9.0
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accelerate==1.13.0
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# Running a notebook as a batch job on the cluster needs no extra package:
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# nbconvert ships with jupyterlab. See cluster/submit_notebook.slurm.
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