These workshops have been/will be repeated a number of times. The Learn page contains the most up-to-date version of workshop materials. This page contains older materials from previously taught workshops.

Quick Links

All Recordings and Chat Files

Workshop 1 - 05/24/2021, 05/25/2021, 05/26/2021

• Laptop Materials
• HPC Materials

Workshop 2 - 05/27/2021, 05/28/2021

• Laptop Materials
• HPC Materials

Workshop 1 - 10/19/2020, 10/21/2020, 10/23/2020

• Laptop Materials
• HPC Materials

Workshop 2 - 10/26/2020, 10/28/2020

• Laptop Materials
• HPC Materials

All Recordings and Chat Files

Due to federal rules regarding videos that are shared with the public (e.g. 508 accessibility requirements for accurate captions, color contrast, etc.) the workshop recordings are only available on the REE-ARS-SCINet-Media Microsoft Stream Channel to USDA employees or collaborators with eAuthentication. We are still working on cutting and timestamping the videos that aren’t posted yet.

Workshop1 Day1 05/24/2021 to be posted, zoom chat

Workshop1 Day2 05/25/2021 to be posted, zoom chat

Workshop1 Day3 05/26/2021 to be posted, zoom chat

Workshop2 Day1 05/27/2021 to be posted, zoom chat

Workshop2 Day2 05/28/2021 to be posted

Workshop1 Day1 10/19/2020 on REE-ARS-SCINet-Media Stream Channel (need eAuth to access), zoom chat part1, zoom chat part2

Workshop1 Day2 10/21/2020 to be posted, zoom chat part1, zoom chat part2

Workshop1 Day3 10/23/2020 to be posted, zoom chat part1, zoom chat part2

Workshop2 Day1 10/26/2020 to be posted, zoom chat part1, zoom chat part2

Workshop2 Day2 10/28/2020 to be posted, zoom chat part1, zoom chat part2

Workshop 1 - 05/24/2021, 05/25/2021, 05/26/2021

Wkshp1 (May 2021) for laptop users (right click the links to download and save to working directory)

Day 1 Workbook: Tutorial1_Image_Processing_Essentials.ipynb

Day 1 Workbook with answers: Tutorial1_Image_Processing_Essentials_complete.ipynb

Day 1 Data: cameraman.png, peppers.png

Day 2 Workbook: Tutorial2_Classical_Machine_Learning.ipynb

Day 2 Workbook with answers: Tutorial2_Classical_Machine_Learning_complete.ipynb

Day 2 Data: CalTech101 dataset 101_ObjectCategories.tar.gz (126 MB; follow link to download), CalTech101 dataset Annotations.tar (13 MB; follow link to download)

(Move the compressed image data folders to your working directory and unzip. Unzip using a terminal (e.g. Windows PowerShell) with tar -xvf filename)

Day 2 Slides: Day2_Rules_ML_DL.pdf

Day 3 Workbook: Tutorial3_Deep_Learning_for_Images.ipynb

Day 3 Workbook with answers: Tutorial3_Deep_Learning_for_Images_complete.ipynb

Day 3 Slides: Day3_CNNs.pdf, Day3_CNN_Epic_Fails.pdf

Wkshp1 (May 2021) for ARS Ceres HPC users

Day1:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/2021-05_session/Tutorial1_Image_Processing_Essentials_complete.ipynb -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/data_images/cameraman.png -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/data_images/peppers.png

Day2:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/2021-05_session/Tutorial2_Classical_Machine_Learning_complete.ipynb
cp /project/shared_files/NMSU-AI-WORKSHOP/*.zip ./
unzip '*.zip'

Note: If you are following this tutorial after the workshop has ended and the NMSU-AI-WORKSHOP shared folder no longer exists, do the following:

• Download and untar the CalTech101 image data to your local machine with the laptop instructions above
• Zip both folders of data (on Windows: right click > Send to > Compressed (zipped) folder)
• Login to Ceres with JupyterHub and upload the zip files (the larger zip will take a few minutes). The upload button is on the JupyterLab navigation pane between the New Folder icon and the Refresh File List icon
• Move the files to your working directory on Ceres and unzip `*.zip'

Day3:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/2021-05_session/Tutorial3_Deep_Learning_for_Images_complete.ipynb

Workshop 2 - 05/27/2021, 05/28/2021

Wkshp2 (May 2021) for laptop users (right click the links to download and save to working directory)

Day 1 Workbook: Tutorial4_Visualizing_and_Modifying_DL_Networks.ipynb

Day 1 Workbook with answers: Tutorial4_Visualizing_and_Modifying_DL_Networks_complete.ipynb

Day 1 Data: my_digits1_compressed.jpg, latest_256_0193.jpg

Day 2 Workbook with answers: Tutorial5_Advanced_DL_Networks_complete.ipynb

Wkshp2 (May 2021) for ARS Ceres HPC users

Day 1:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/2021-05_session/Tutorial4_Visualizing_and_Modifying_DL_Networks_complete.ipynb -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/data_images/my_digits1_compressed.jpg -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/data_images/latest_256_0193.jpg

Day 2:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/2021-05_session/Tutorial5_Advanced_DL_Networks_complete.ipynb

Workshop 1 - 10/19/2020, 10/21/2020, 10/23/2020

Wkshp1 (Oct 2020) for laptop users (right click the links to download and save to working directory)

Day 1 Workbook: Tutorial1_Image_Processing_Essentials.ipynb

Day 1 Data: cameraman.png, peppers.png

Day 1 static notebook with outputs/answers: Tutorial1_Image_Processing_Essentials_complete.html

Day 1 instructor ipynb with ad hoc cells added during instruction: Tutorial1_Image_Processing_Essentials_Boucheron.ipynb

Day 2 Workbook: Tutorial2_Classical_Machine_Learning.ipynb (right click the link to download)

Day 2 Data: CalTech101 dataset 101_ObjectCategories.tar.gz (126 MB; follow link to download), CalTech101 dataset Annotations.tar (13 MB; follow link to download)

(Move the compressed image data folders to your working directory and unzip. Unzip using a terminal (e.g. Windows PowerShell) with tar -xvf filename)

Day 2 Slides: Day2_Rules_ML_DL.pdf

Day 2 static notebook with outputs/answers: Tutorial2_Classical_Machine_Learning_complete.html

Day 2 instructor ipynb with ad hoc cells added during instruction: Tutorial2_Classical_Machine_Learning_Boucheron.html

Day 3 Workbook: Tutorial3_Deep_Learning_for_Images.ipynb

Day 3 Slides: Day3_CNNs.pdf, Day3_CNN_Epic_Fails.pdf

Day 3 static notebook with outputs/answers: Tutorial3_Deep_Learning_for_Images_complete.html

Day 3 instructor ipynb with ad hoc cells added during instruction: Tutorial3_Deep_Learning_for_Images_Boucheron.ipynb

Wkshp1 (Oct 2020) for ARS Ceres HPC users

Day1:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/Tutorial1_Image_Processing_Essentials.ipynb -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/data_images/cameraman.png -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/data_images/peppers.png

Day2:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/Tutorial2_Classical_Machine_Learning.ipynb
cp /project/shared_files/NMSU-AI-WORKSHOP/*.zip ./
unzip '*.zip'

Note: If you are following this tutorial after the workshop has ended and the NMSU-AI-WORKSHOP shared folder no longer exists, do the following:

• Download and untar the CalTech101 image data to your local machine with the laptop instructions above
• Zip both folders of data (on Windows: right click > Send to > Compressed (zipped) folder)
• Login to Ceres with JupyterHub and upload the zip files (the larger zip will take a few minutes). The upload button is on the JupyterLab navigation pane between the New Folder icon and the Refresh File List icon
• Move the files to your working directory on Ceres and unzip `*.zip'

Day3:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/Tutorial3_Deep_Learning_for_Images.ipynb

Workshop 2 - 10/26/2020, 10/28/2020

Wkshp2 (Oct 2020) for laptop users (right click the links to download and save to working directory)

Day 1 Workbook: Tutorial4_Visualizing_and_Modifying_DL_Networks.ipynb

Day 1 Data: my_digits1_compressed.jpg, latest_256_0193.jpg

Day 1 static notebook with outputs/answers: Tutorial4_Visualizing_and_Modifying_DL_Networks_complete.html

Day 1 instructor ipynb with ad hoc cells added during instruction: Tutorial4_Visualizing_and_Modifying_DL_Networks_Boucheron.ipynb

Day 2 Workbook: Tutorial5_Advanced_DL_Networks.ipynb

Day 2 Data: https://pjreddie.com/media/files/yolov3.weights (236 MB), https://3qeqpr26caki16dnhd19sv6by6v-wpengine.netdna-ssl.com/wp-content/uploads/2019/03/zebra.jpg

Day 2 static notebook with outputs/answers: Tutorial5_Advanced_DL_Networks_complete.html

Day 2 instructor ipynb with ad hoc cells added during instruction: Tutorial5_Advanced_DL_Networks_complete.ipynb

Wkshp2 (Oct 2020) for ARS Ceres HPC users

Day 1:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/Tutorial4_Visualizing_and_Modifying_DL_Networks.ipynb -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/data_images/my_digits1_compressed.jpg -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/data_images/latest_256_0193.jpg

Day 2:

curl -O https://kerriegeil.github.io/NMSU-USDA-ARS-AI-Workshops/tutorials/Tutorial5_Advanced_DL_Networks.ipynb -O https://pjreddie.com/media/files/yolov3.weights -O https://3qeqpr26caki16dnhd19sv6by6v-wpengine.netdna-ssl.com/wp-content/uploads/2019/03/zebra.jpg