Tuit catalog

Synthesis notes of video analyses, assessed and condensed, in French and English.

54,278 tuit · 964 channels · 42 domains · Last update: Nov 2, 2026
Granular Thema (1,936)
54278 tuit · page 564/1357
Applied Sciences & Engineering Engineering & Technology
EN

The Deadliest Design Mistakes in History

John Mauriello
30 min
★ ★ ★ ★ ☆ 4/5
Design FailuresProduct SafetyHuman Factors
Formal & Physical Sciences AI — Models & Research
EN

Shapley Additive Explanations (SHAP)

Machine learning classroom
20 min
★ ★ ★ ★ ☆ 4/5
SHAPExplainable AIFeature Attribution
Applied Sciences & Engineering AI — Models & Research
EN

Plugin Claude Cowork : Vos collaborateurs IA !

Claude Cowork Plugin: Your AI collaborators!

Renaud Dékode
25 min
★ ★ ★ ★ ☆ 4/5
Claude CoworkAI AgentsPlugins
Humanities, Social Sciences & Thought Computing & Cybersecurity
EN

Organización digital

Digital organization

Habilidades de Inteligencia Artificial Aplicada Uk
117 min
★ ★ ☆ ☆ ☆ 2/5
Digital OrganizationProductivityGoogle Workspace
Formal & Physical Sciences Medicine & Health
EN

MLT | Week-3 | Session-2

Karthik Thiagarajan
153 min
★ ★ ★ ★ ☆ 4/5
K-MeansClusteringVoronoi Regions
Applied Sciences & Engineering Society & Culture
EN

MENACE | EP03

Evidicus
50 min
★ ★ ★ ☆ ☆ 3/5
MENACETactical GameGameplay
Humanities, Social Sciences & Thought Arts & Architecture
EN

Lunchtime Talk – Marta Bielinska 2/27/26

Marta Bielinska
50 min
★ ★ ★ ★ ☆ 4/5
Philosophy of ScienceLaws of NatureBest System Approach
Formal & Physical Sciences AI — Models & Research
EN

Intrinsically interpretable models

Machine learning classroom
14 min
★ ★ ★ ★ ☆ 4/5
InterpretabilityMachine LearningLogistic Regression
Formal & Physical Sciences AI — Models & Research
EN

Gradient-based explanations (saliency maps)

Machine learning classroom
15 min
★ ★ ★ ★ ☆ 4/5
Explainable AISaliency MapsGradient-Based Explanations
Formal & Physical Sciences AI — Models & Research
EN

Counterfactual explanations

Machine learning classroom
11 min
★ ★ ★ ★ ☆ 4/5
Counterfactual ExplanationsInterpretabilityMachine Learning