AI — Models & Research

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Applied Sciences & Engineering AI — Models & Research
EN

MLP Live session | Week 2

22t1 cs2008
130 min
★ ★ ★ ☆ ☆ 3/5
Machine LearningData ScienceTutorial
Formal & Physical Sciences AI — Models & Research
EN

Comprendre ce qu'il se passe quand on prompt

Understanding what happens when you prompt

Renaud Dékode
32 min
★ ★ ★ ★ ☆ 4/5
LLMPrompt EngineeringTokenization
Formal & Physical Sciences AI — Models & Research
EN

MLT | Week-1 | Session-2

MLT cs2007 (instructor)
113 min
★ ★ ★ ★ ☆ 4/5
PCADimensionality ReductionMachine Learning
Applied Sciences & Engineering AI — Models & Research
EN

MLP Project Orientation | 26T1

Machine Learning Practice
158 min
★ ★ ★ ☆ ☆ 3/5
KaggleMachine LearningCourse Project
Formal & Physical Sciences AI — Models & Research
EN

PyTorch Tutorial

Jamison Meindl
29 min
★ ★ ★ ★ ☆ 4/5
PyTorchDeep LearningTensors
Applied Sciences & Engineering AI — Models & Research
EN

Lec 09. Hacker's Guide to Deep Learning

Phillip Isola
75 min
★ ★ ★ ★ ☆ 4/5
Deep LearningPractical TipsTraining Neural Networks
Formal & Physical Sciences AI — Models & Research
EN

Lec 08. Architectures: Transformers

Phillip Isola
74 min
★ ★ ★ ★ ★ 5/5
TransformersAttentionTokens
Formal & Physical Sciences AI — Models & Research
EN

Lec 05. Architectures: Graphs

Phillip Isola
81 min
★ ★ ★ ★ ★ 5/5
Graph Neural NetworksMessage PassingArchitecture
Formal & Physical Sciences AI — Models & Research
EN

Lec 04. Architectures: Grids

Sara Beery
83 min
★ ★ ★ ★ ☆ 4/5
Deep LearningConvolutional Neural NetworksArchitectures
Formal & Physical Sciences AI — Models & Research
EN

Lec 03. Approximation Theory

Jeremy Bernstein
82 min
★ ★ ★ ★ ★ 5/5
Approximation TheoryDeep LearningNeural Networks
Formal & Physical Sciences AI — Models & Research
EN

Lec 02. How to Train a Neural Net

Sara Beery
79 min
★ ★ ★ ★ ★ 5/5
Deep LearningNeural NetworksBackpropagation