Refer to this User Guide for instructions on loading required packages and launching Jupyter Notebook in Expanse.
The following table lists the notebooks in alphabetical order. To view by type, use the links below:
| Notebook Project | Notebook | Type | Required (Sub) Modules |
|---|---|---|---|
| CUDA_GPU_Computing_Pi | cuda_gpu_nvidia_computing_pi_solution.ipynb | GPU, Parallel | numba, math, numpy, cuda |
| CUDA_GPU_Distance_Matrix | cuda_gpu_nvidia_distance_matrix_solution.ipynb | GPU, Parallel | numba, math, numpy, cuda |
| CUDA_GPU_Law_Of_Cosines | cuda_gpu_nvidia_law_of_cosines_solution.ipynb | GPU, Parallel | numba, math, numpy, vectorize, cuda |
| Clustering_Visualizations | Introduction_to_Clustering.ipynb | CPU, Serial | scikit-learn, numpy, matplotlib, sciPy, make_blobs, KMeans, dendrogram, linkage, AgglomerativeClustering |
| Dask_Graph_CPU | dask_graphs_CPU.ipynb | CPU, Parallel | dask |
| Dask_Graph_GPU | dask_graphs_GPU.ipynb | GPU, Parallel | dask, cupy, dask.array, array |
| Data_Analysis | data_analysis_pandas.ipynb | CPU, Serial | numpy, pandas |
| Data_Analysis_Cupy | data_analysis_cupy.ipynb | GPU, Parallel | cupy, cudf, pandas, numpy |
| Decision_Trees | Decision trees.ipynb | CPU, Serial | scikit-learn, tree, sklearn.datasets, graphviz, load_iris |
| Graphs&Networks | NetworkX.ipynb | CPU, Serial | NetworkX, matplotlib.pyplot, networkx, write_dot, networkx.drawing.nx_pydot, networkx |
| Hello_World_CPU | hello_world_cpu.ipynb | CPU, Serial | |
| Hello_World_GPU | hello_world_gpu.ipynb | GPU, Serial | |
| Image_Processing | Pillow.ipynb | CPU, Serial | PIL, Image, sys, ImageFilter, ImageEnhance |
| Matplotlib_Intro | matplotlib_intro.ipynb | CPU, Serial | matplotlib, matplotlib.pyplot, numpy |
| Multithreaded_Processing_CPU | multithreaded_processing.ipynb | CPU, Parallel | mkl, numpy, dask.array |
| NumPy_Intro | numpy_intro.ipynb | CPU, Serial | numpy, operator, add, matplotlib.pyplot, collections, Counter |
| Python_Data_Analysis_Library | PandasCSV.ipynb | CPU, Serial | IPython.display, Image, pandas |
| String_Processing | Regression.ipynb | CPU, Serial | sklearn, linear_model, mean_squared_error, r2_score, sklearn.datasets, load_diabetes, numpy, matplotlib.pyplot, pandas, scipy, stats |
| Tensorflow_Image_Classification | Image Classification.ipynb | CPU, GPU, Parallel | tensorflow, matplotlib.pyplot, numpy, PIL, keras, layers, tensorflow.keras, tensorflow.keras.models, Sequential, pathlib |
| Tensorflow_Simple_Training | SimpleTraining.ipynb | CPU, GPU, Parallel | tensorflow, numpy, csv, matplotlib.pyplot |