(Open) Webinar - Introduction to ML/DL Theory - Explore the foundational theory behind Machine Learning (ML) and Deep Learning (DL) in a geospatial context
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https://events.teams.microsoft.com/event/f6f7b736-1fa2-4934-aee9-895685232fb4@05c95b33-90ca-49d5-b644-288b930b912b <-- shared webina registration
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H/T Eric Loubier | DG, Canada Centre for Mapping and Earth Observation
“🌎 GeoAI Webinar Series
March 5, 2026 (11:00 am–3:00 pm ET)
Module #1: Introduction to ML/DL Theory
• Explore the foundational theory behind Machine Learning (ML) and Deep Learning (DL) in a geospatial context…”
#webinar #open #free #GeoAI #UNGGIM #ArtificialIntelligence #Geospatial #Webinar #Canada #Americas #eLearning #onlinelearning #AI #NorthAmerica #Algorithms #Architectures #ML #DL #GIS #spatial #mapping #machinelearning #deeplearning #usecase #workflow #spatialdata #remotesensing

(Open) Webinar - Introduction to ML/DL Theory - Explore the foundational theory behind Machine Learning (ML) and Deep Learning (DL) in a geospatial context
--
https://events.teams.microsoft.com/event/f6f7b736-1fa2-4934-aee9-895685232fb4@05c95b33-90ca-49d5-b644-288b930b912b <-- shared webina registration
--
H/T Eric Loubier | DG, Canada Centre for Mapping and Earth Observation
“🌎 GeoAI Webinar Series
March 5, 2026 (11:00 am–3:00 pm ET)
Module #1: Introduction to ML/DL Theory
• Explore the foundational theory behind Machine Learning (ML) and Deep Learning (DL) in a geospatial context…”
#webinar #open #free #GeoAI #UNGGIM #ArtificialIntelligence #Geospatial #Webinar #Canada #Americas #eLearning #onlinelearning #AI #NorthAmerica #Algorithms #Architectures #ML #DL #GIS #spatial #mapping #machinelearning #deeplearning #usecase #workflow #spatialdata #remotesensing

AI pet peeve: everyone equates artificial neural networks and gradient-based optimization with brains, minds, and thinking.

ANNs are big, parameterized math equations that we configure with an algorithm. Living neurons are intelligent agents that manage their own behavior and relationships autonomously. Human brains definitely aren't attempting to differentiate through their interactions in the physical world, because that isn't possible. They don't do backprop, either.

Deep learning is its own thing. Brains are something else. It's hard to figure out how they compare when we keep pretending they're the same.

#ai #deeplearning

#lispyGopherClimate Sunday-morning-in-Europe 8am UTC+0
#archive
https://toobnix.org/w/iAwuN4MGuaiHTDDCibhb21

Two weeks from now, @cdegroot will be on the lispy gopher climate show to discuss their new lisp book, The Genius of Lisp. I got my review copy and will share the ToC.

I am not going to spoil the fascinating foreword by rpg but it relates to my symbolic #lisp #ffnn #deepLearning

https://screwlisp.small-web.org/complex/lisp-feedforward-deep-learning-example/

so I will mention that and my #ROC interpretation of deep learning inferencing.
#programming

#lispyGopherClimate Sunday-morning-in-Europe 8am UTC+0
#archive
https://toobnix.org/w/iAwuN4MGuaiHTDDCibhb21

Two weeks from now, @cdegroot will be on the lispy gopher climate show to discuss their new lisp book, The Genius of Lisp. I got my review copy and will share the ToC.

I am not going to spoil the fascinating foreword by rpg but it relates to my symbolic #lisp #ffnn #deepLearning

https://screwlisp.small-web.org/complex/lisp-feedforward-deep-learning-example/

so I will mention that and my #ROC interpretation of deep learning inferencing.
#programming

Yeesh, okay it is out and I can stop telling you I am going to write it.

https://screwlisp.small-web.org/complex/lisp-feedforward-deep-learning-example/

#deepLearning #symbolic #ffnn pure ansi #commonLisp

The example deliberately causes a hallucination programmed into the training data via simple #roc reasoning. To my knowledge the ROC interpretation of ffnn inference is original to me, here.

The hallucination is in both lockstep and single #neuralnet activations.

Be the first to complain my #DL works on subregions of jagged lists! #programming

Yeesh, okay it is out and I can stop telling you I am going to write it.

https://screwlisp.small-web.org/complex/lisp-feedforward-deep-learning-example/

#deepLearning #symbolic #ffnn pure ansi #commonLisp

The example deliberately causes a hallucination programmed into the training data via simple #roc reasoning. To my knowledge the ROC interpretation of ffnn inference is original to me, here.

The hallucination is in both lockstep and single #neuralnet activations.

Be the first to complain my #DL works on subregions of jagged lists! #programming