Deep learning in Google Earth Engine with Jake Wilkins

In this video, Robin catches up with Jake Wilkins to learn about Deep learning in Google Earth Engine. Jake has been building commercial Earth Engine applications for the past three years and in this conversation he describes the pros and cons of several approaches to using deep learning models with Earth Engine. Note that the audio of this conversation is released as a podcast, listed below
* www.satellite-image-deep-lear...
* / jake-wilkins-2b482b225
* earthengine.google.com/
Bio: Jake is a Software Engineer and Data Scientist based in London, UK. He has been building commercial Google Earth Engine applications for the past three years. His significant contributions include the no-code platform, Earth Blox, and the climate monitoring platform STRATA for UNEP (United Nations Environmental Programme). Alongside this, Jake has consistently developed his skills in machine learning, and a notable accomplishment in this field is winning the Earth-i hackathon last year. Jake has a deep passion for addressing the climate crisis and is committed to making Earth Observation more accessible to combat it.

[@jakewilkins1774]

Thanks again Robin, it was a pleasure to be a guest on the podcast, and I’m hoping this brings more to the Earth Engine party. Since recording the podcast, Google has released some notable features to Earth Engine - the BigQuery Connector, Data Extraction APIs and the VertexAI Connector - the first improves geometry and vector processing and the latter supersedes the AI Platform connector. I have provided an update comment in the resource document I show in the video. I also have some personal details in there, so please reach out for anything!

[@MuddasirShah]

Great explanation. Thank you!! Shared

[@ameral-faraj173]

Hi guys, is there ready Google API to be used and publish a video project using Google Earth Engine?

[@kulsoompanhwar190]

kindly share script if it is possible

[@geologistdinesh]

Dear sir send me script to study thanks