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Machine Learning and Neural Networks

Fundamentals and Applications

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Machine Learning and Neural Networks
Fundamentals and Applications
1 / 6
Machine Learning and Neural Networks
Fundamentals and Applications
Machine Learning and Neural Networks1 / 6
What is Machine Learning?
Definition and Types
  • ●
    Machine Learning is a subset of Artificial Intelligence that enables systems to learn from data
  • ●
    Types: Supervised, Unsupervised, Reinforcement Learning
  • ●
    Supervised Learning: Predicting outcomes based on labeled data
  • ●
    Unsupervised Learning: Identifying patterns in unlabeled data
  • ●
    Reinforcement Learning: Learning from rewards and penalties
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Key Statistics
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100 billionMarket Size
20% per yearGrowth Rate
100+ industriesApplications
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Neural Network Architecture
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Number of Neurons
10
Input Layer
20
Hidden Layer
5
Output Layer
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History of Neural Networks
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1

1940s: McCulloch-Pitts Neuron

First artificial neuron model

2

1950s: Perceptron

First multi-layer neural network

3

1980s: Backpropagation

First efficient training algorithm

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Applications of Neural Networks
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Total100
Percentage of Applications
Image Recognition
30%
Natural Language Processing
20%
Speech Recognition
50%
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