NASA´s Applied Remote Sensing Training (ARSET): PART 3 | TIMELINE down below! Fundamentals of Machine Learning for Earth Science Model Tuning, Parameter Optimization, & Additional Machine Learning Algorithms, Part 3/3 | 2023 TIMELINE down below! Part 3: Model Tuning, Parameter Optimization, and Additional Machine Learning Algorithms PART...

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NASA´s Applied Remote Sensing Training (ARSET): PART 3 TIMELINE down below! Fundamentals of Machine Learning for Earth Science Model Tuning, Parameter Optimization, & Additional Machine Learning Algorithms, Part 3/3 2023 TIMELINE down below! Part 3: Model Tuning, Parameter Optimization, and Additional Machine Learning Algorithms PART 1-Overview of Machine Learning: PART 2-Training Data and Land Cover Classification Example: Trainers: Jordan A. Caraballo-Vega, Caleb Spradlin, Jian Li, Jules Kouatchou  -Overview of model tuning -Overview of parameter optimization  -Exercise to optimize existing model  -Overview of model explainability and interpretability  -Overview of additional machine learning algorithms  -Hands on Jupyter Notebook Exercise: Improvements to MODIS (Moderate Resolution Imaging Spectroradiometer) Water Classification Model -Post-session assignment   -Q&A Session You can access all training materials from this webinar series on the training webpage: This training was created by NASA's Applied Remote Sensing Training Program (ARSET). ARSET is a part of NASA's Applied Science's Capacity Building Program. Learn more about ARSET: Timeline: Coordinator: Brock Blevins 0:00 Introduction Part 3: Model Tuning, Parameter Optimization, and Additional Machine Learning Algorithms 0:27 Training Objectives 1:09 Prerequisites Part 1: Google Drive & Google Colab 1:50 Training Schedule Part 3 Trainer Jordan A. Caraballo-Vega 2:30 Model Tuning, Parameter Optimization, and Additional Machine Learning Algorithms 2:55 Session 3 Outline Resources for this training: 3:43 Training Objectives 4:17 Overview of Model Tuning and Optimization Summary from Session 2 - Part 2:  11:25 Techniques for Model Tuning 16:10 Exercise: Tuning and Optimization of the Random Forest Model in Google Colab Trainer Caleb S. Spradin 31:35 Model Explainability and Interpretability - XAI (Explainable Artificial Intelligence) 38:16 Attention and Explainability - XAI 39:15 Exercise: Model Explainability and Interpretability - XAI in Google Colab Trainer Jordan A. Caraballo-Vega 56:07 Exercise: Introduction to AutoML and Closing Remarks 1:09:07 Closing Remarks (Homeworks & Certificate - expired May 25, 2023) 1:16:40 Contacts Trainer  Training Website: ARSET Website: SERVIR (NASA sister programs): About SERVIR: About DEVELOP: NASA DEVELOP Projects: 1:17:20 Questions? - Q&A Session - Questions & Answers Part 3 Part 1 : Overview of Machine Learning - Part 2: Trainig Data and Land Cover Classification Example - Part 3: Model Tuning, Parameter Optimization, and Additional Machine Learning Algorithms - Homework: Independent practice and application NASA Videos: Source: Resources for this training: You can access all training materials from this webinar series on the training webpage: This training was created by NASA's Applied Remote Sensing Training Program (ARSET). ARSET is a part of NASA's Applied Science's Capacity Building Program. Learn more about ARSET:

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NASA´s Applied Remote Sensing Training (ARSET): PART 3 TIMELINE down below! Fundamentals of Machine Learning for Earth Science Model Tuning, Parameter Optimization, & Additional Machine Learning Algorithms, Part 3/3 2023 TIMELINE down below! Part 3: Model Tuning, Parameter Optimization, and Additional Machine Learning Algorithms PART 1-Overview of Machine Learning: PART 2-Training Data and Land Cover Classification Example: Trainers: Jordan A. Caraballo-Vega, Caleb Spradlin, Jian Li, Jules Kouatchou  -Overview of model tuning -Overview of parameter optimization  -Exercise to optimize existing model  -Overview of model explainability and interpretability  -Overview of additional machine learning algorithms  -Hands on Jupyter Notebook Exercise: Improvements to MODIS (Moderate Resolution Imaging Spectroradiometer) Water Classification Model -Post-session assignment   -Q&A Session You can access all training materials from this webinar series on the training webpage: This training was created by NASA's Applied Remote Sensing Training Program (ARSET). ARSET is a part of NASA's Applied Science's Capacity Building Program. Learn more about ARSET: Timeline: Coordinator: Brock Blevins 0:00 Introduction Part 3: Model Tuning, Parameter Optimization, and Additional Machine Learning Algorithms 0:27 Training Objectives 1:09 Prerequisites Part 1: Google Drive & Google Colab 1:50 Training Schedule Part 3 Trainer Jordan A. Caraballo-Vega 2:30 Model Tuning, Parameter Optimization, and Additional Machine Learning Algorithms 2:55 Session 3 Outline Resources for this training: 3:43 Training Objectives 4:17 Overview of Model Tuning and Optimization Summary from Session 2 - Part 2:  11:25 Techniques for Model Tuning 16:10 Exercise: Tuning and Optimization of the Random Forest Model in Google Colab Trainer Caleb S. Spradin 31:35 Model Explainability and Interpretability - XAI (Explainable Artificial Intelligence) 38:16 Attention and Explainability - XAI 39:15 Exercise: Model Explainability and Interpretability - XAI in Google Colab Trainer Jordan A. Caraballo-Vega 56:07 Exercise: Introduction to AutoML and Closing Remarks 1:09:07 Closing Remarks (Homeworks & Certificate - expired May 25, 2023) 1:16:40 Contacts Trainer  Training Website: ARSET Website: SERVIR (NASA sister programs): About SERVIR: About DEVELOP: NASA DEVELOP Projects: 1:17:20 Questions? - Q&A Session - Questions & Answers Part 3 Part 1 : Overview of Machine Learning - Part 2: Trainig Data and Land Cover Classification Example - Part 3: Model Tuning, Parameter Optimization, and Additional Machine Learning Algorithms - Homework: Independent practice and application NASA Videos: Source: Resources for this training: You can access all training materials from this webinar series on the training webpage: This training was created by NASA's Applied Remote Sensing Training Program (ARSET). ARSET is a part of NASA's Applied Science's Capacity Building Program. Learn more about ARSET:

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