Name		Name	Last commit message	Last commit date
parent directory ..
01_Introduction_to_RAPIDS.ipynb		01_Introduction_to_RAPIDS.ipynb
02_Introduction_to_cuDF.ipynb		02_Introduction_to_cuDF.ipynb
03_Introduction_to_Dask.ipynb		03_Introduction_to_Dask.ipynb
04_Introduction_to_Dask_using_cuDF_DataFrames.ipynb		04_Introduction_to_Dask_using_cuDF_DataFrames.ipynb
06_Introduction_to_Supervised_Learning.ipynb		06_Introduction_to_Supervised_Learning.ipynb
07_Introduction_to_XGBoost.ipynb		07_Introduction_to_XGBoost.ipynb
09_Introduction_to_Dimensionality_Reduction.ipynb		09_Introduction_to_Dimensionality_Reduction.ipynb
10_Introduction_to_Clustering.ipynb		10_Introduction_to_Clustering.ipynb
11_Introduction_to_Strings.ipynb		11_Introduction_to_Strings.ipynb
12_Introduction_to_Exploratory_Data_Analysis_using_cuDF.ipynb		12_Introduction_to_Exploratory_Data_Analysis_using_cuDF.ipynb
13_Introduction_to_Time_Series_Data_Analysis_using_cuDF.ipynb		13_Introduction_to_Time_Series_Data_Analysis_using_cuDF.ipynb
14_Introduction_to_Machine_Learning_using_cuML.ipynb		14_Introduction_to_Machine_Learning_using_cuML.ipynb
README.md		README.md

README.md

Tutorial

Notebook Title	Description
01_Introduction_to_RAPIDS	This notebook shows at a high level what each of the packages in RAPIDS are as well as what they do.
02_Introduction_to_cuDF	This notebook shows how to work with cuDF DataFrames in RAPIDS.
03_Introduction_to_Dask	This notebook shows how to work with Dask using basic Python primitives like integers and strings.
04_Introduction_to_Dask_using_cuDF_DataFrames	This notebook shows how to work with cuDF DataFrames using Dask.
05_Introduction_to_Dask_cuDF	This notebook shows how to work with cuDF DataFrames distributed across multiple GPUs using Dask.
06_Introduction_to_Supervised_Learning	This notebook shows how to do GPU accelerated Supervised Learning in RAPIDS.
07_Introduction_to_XGBoost	This notebook shows how to work with GPU accelerated XGBoost in RAPIDS.
08_Introduction_to_Dask_XGBoost	This notebook shows how to work with Dask XGBoost in RAPIDS.
09_Introduction_to_Dimensionality_Reduction	This notebook shows how to do GPU accelerated Dimensionality Reduction in RAPIDS.
10_Introduction_to_Clustering	This notebook shows how to do GPU accelerated Clustering in RAPIDS.
11_Introduction_to_Strings	This notebook shows how to use cuDF to process text data.
12_Introduction_to_Exploratory_Data_Analysis	This notebook shows how to perform basic EDA with cuDF DataFrames
13_Introduction_to_Time_Series_Data_Analysis_using_cuDF	This notebook shows how to do EDA on time-series DataFrame with cuDF
14_Introduction_to_Machine_Learning_using_cuML	This notebook provides an introduction to core machine learning techniques with cuML

Coming soon!

Notebook Title	Description
15_Introduction_to_Model_Evaluation_and_Hyperparameter_Tuning	To be edited.
16_Predicting_Customer_Transactions	To be edited.
17_Predicting_Market_Response	To be edited.
18_Predicting_Repeat_Buyers	To be edited.
19_Predicting_Store_Sales	To be edited.
20_Predicting_Store_Sales_in_Stormy_Weather	To be edited.
21_Classifying_Trip_Types	To be edited.
22_Introduction_to_Exploratory_Data_Analysis	To be edited.
23_Introduction_to_Data_Visualization	To be edited.
24_Introduction_to_Graph_Analytics	To be edited.
25_Introduction_to_Collaborative_Filtering	To be edited.
26_Introduction_to_Deep_Learning	To be edited.
27_Introduction_to_Profiling	To be edited.
28_Introduction_to_Scaling_to_Multiple_Nodes	To be edited.
29_Introduction_to_Spark	To be edited.
30_Advanced_Usage	To be edited.
31_Best_Practices	To be edited.