This class was created by Brainscape user Josh Davidson. Visit their profile to learn more about the creator.

Decks in this class (18)

Week 2 - Search with A* & MCTS
Intelligent agents 1,
Static agents vs learning 2,
Breadth first 3
25  cards
3 - Neural Net for modern AI
Action potential 1,
Perceptron 2,
Perceptron learning rule 3
14  cards
3 - Backpropagation in computation graphs
Computational graph 1,
Partial derivative 2,
Chain rule 3
13  cards
4/5 - Deep Convolutional Neural Networks
Deep learning 1,
Overfitting in deep learning para...,
Shape analogy for layers abstract...
46  cards
5/6 - Unsupervised Learning in the era of generative AI
Unsupervised learning 1,
Unsupervised v supervised 2,
Clustering 3
21  cards
6 - How smart is deep learning
What might happen when you add ra...,
Clever hans 2
2  cards
6 - Probability and Bayes Theorem
Consider r and b as boxes 1,
Consider r and b as boxes 2,
Consider r and b as boxes 3
17  cards
7 - Reinforcement Learning
4 things rl is built on 1,
Policy 2,
Reward signal 3
21  cards
7 - Reinforcement Learning 2
Finite markov design processes 1,
Markov property hint states depen...,
Markov chains 3
17  cards
7- Reinforcement Learning - SARSA/Q
Sarsa 1,
Sarsa pesudocode 2,
Q learning 3
5  cards
8/9 - Approximate Methods and Deep RL
2 problems with tabular approache...,
Approximate methods seek to appro...,
How can approximation be improved 3
10  cards
8 - GPU Acceleration and AI HW
Why is ai computationally expensi...,
Flops 2,
Tops 3
17  cards
9 - Quantifying intelligence in modern AI
Gofai 1,
Weaknesses of gofai 2,
Digital twinning 3
5  cards
10 - Evolutionary Computation Review
Evolutionary algorithms 1,
In this module assume that the di...,
Main idea of evo algos steps 3
34  cards
10 - Neuroevolution
Evolving weights 1,
Advantages of neuroevolution vs b...,
Evolving architectures in terms o...
19  cards
11 - LLMs
What is attention 1,
Attention is all you need 2,
How do neural nets process words ...
20  cards
11- bayesian networks and causality
Bayesian network defintion 1,
How are bayesian networks represe...,
Bayesian network example in medic...
16  cards
12 - Continual/Lifelong Machine Learning
Traditional machine learning dev ...,
Problem with traditional ai syste...,
Catastrophic forgetting 3
8  cards

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Advanced AI

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