Introduction to ML, Deep Learning and Google Colab

Table of contents

Session Agenda

Date: 08/08/2023
Instructor(s): Lilly Thomas & Ryan Avery

Time Topics Presenter
07:30 - 08:00
  • Checklist of trainees
Moderator:
  • Marvin Quispe (ACCA)
08:00 - 08:30
  • Opening remarks
Moderator:
  • Milagros Becerra (ACCA)
Speaker:
  • Vanesa Martin (NASA)
  • Carlos Gasco (CIAT/SAMZ)
  • Sidney Novoa (ACCA)
  • Patrick Venail (UTEC)
08:30 - 09:00
  • Opening photo
Moderator:
  • Claudia Hurtado (ACCA)
09:00 - 09:30
  • Overview of the TF Training
  • Goals: Capacity Building
Moderator:
  • Vanesa Martin (NASA)
  • Milagros Becerra (ACCA)
09:30 - 10:30
  • What is your Application Area? Overview
  • Hub presentations SERVIR Amazonia services and ML
Lead:
  • Milagros Becerra (ACCA)
Moderator:
  • Vanesa Martin (NASA)
  • Marvin Quispe (ACCA)
  • Osmar Yupanqui (ACCA)
10:30 - 11:00 Coffee Break -
11:00 - 12:00
  • Introduction to Machine Learning, Deep Learning and Artificial Intelligence
Moderator:
  • Osmar Yupanqui (ACCA)
Presenter:
  • Lilly Thomas(Development Seed)
  • Ryan Avery (Development Seed)
12:00 - 13:00
  • Introduction to Google Colab, Tensorflow 2.0 and Keras Library
Moderator:
  • Osmar Yupanqui (ACCA)
Presenter:
  • Lilly Thomas(Development Seed)
13:00 - 14:15 Lunch -
14:15 - 15:00
  • Overview of the building blocks (tensors) of TensorFlow (Tensors), main methods, functions and datasets
Moderator:
  • Osmar Yupanqui (ACCA)
Presenter:
  • Lilly Thomas(Development Seed)
15:00 - 15:40 Break -
15:40 - 17:00
  • Integrating TensorFlow with Google Earth Engine and Google Cloud Platform
Moderator:
  • Osmar Yupanqui (ACCA)
Presenter:
  • Lilly Thomas(Development Seed)
  • Ryan Avery (Development Seed)
17:00 - 17:20
  • Day 1 wrap up
Moderator:
  • Vanesa Martin (NASA)

Content

Introduction to Machine Learning, Deep Learning and Artificial Intelligence:

Introduction to Google Colab, Tensorflow 2.0 and Keras Library:

Overview of the building blocks (tensors) of TensorFlow (Tensors), main methods, functions and datasets:

Integrating TensorFlow with Google Earth Engine and Google Cloud Platform: