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Machine Learning

Machine Learning is a subfield of Artificial intelligence

"Learning machines to imitate human intelligence"

Machine Learning (ML)

Traditional programming uses algorithms to produce results from data:

Data + Algorithms = Results

Machine learning creates algorithms from data and results:

Data + Results = Algorithms

Neural Networks (NN)

Neural Networks is

  • A programming technique
  • A method used in machine learning
  • A software that learns from mistakes

Neural Networks are based on how the human brain works: Neurons are sending messages to each other. While the neurons are trying to solve a problem (over and over again), it is strengthening the connections that lead to success and diminishing the connections that lead to failure.

Perceptrons

The Perceptron defines the first step into Neural Networks.

It represents a single neuron with only one input layer, and no hidden layers.

Learn how to program a perceptron .

Neural Networks

Neural Networks are Multi-Layer Perceptrons .

In its simplest form, a neural network is made up from:

  • An input layer (yellow)
  • A hidden layer (blue)
  • An output layer (red)

In the Neural Network Model , input data (yellow) are processed against a hidden layer (blue) before producing the final output (red).

The First Layer : The yellow perceptrons are making simple decisions based on the input. Each single decision is sent to the perceptrons in the next layer.

The Second Layer : The blue perceptrons are making decisions by weighing the results from the first layer. This layer make more complex decisions at a more abstract level than the first layer.

Deep Neural Networks

Deep Neural Networks are made up of several hidden layers of neural networks that perform complex operations on massive amounts of data.

Each successive layer uses the preceding layer as input.

For instance, optical reading uses low layers to identify edges, and higher layers to identify letters.

In the Deep Neural Network Model , input data (yellow) are processed against a hidden layer (blue) and modified against more hidden layers (green) to produce the final output (red).

The First Layer : The yellow perceptrons are making simple decisions based on the input. Each single decision is sent to the perceptrons in the next layer.

The Second Layer : The blue perceptrons are making decisions by weighing the results from the first layer. This layer make more complex decisions at a more abstract level than the first layer.

The Third Layer : Even more complex decisions are made by the green perceptrons.

Deep Learning (DL)

Deep Learning is a subset of Machine Learning.

Deep Learning is responsible for the AI boom of the last years.

Deep learning is an advanced type of ML that handles complex tasks like image recognition.

Machine LearningDeep Learning
A subset of AIA subset of Machine Learning
Uses smaller data setsUses larger datasets
Trained by humansLearns on its own
Creates simple algorithmsCreates complex algorithms

Chapter

Back to Machine Learning

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Artificial Intelligence

This chapter

Overview
16

Lessons

69m

Read time

1. Machine Learning2. Artificial Intelligence3. Machine Learning Languages4. Machine Learning in JavaScript5. Linear Graphs6. Scatter Plots7. Perceptrons8. Pattern Recognition9. Testing a Perceptron10. Machine Learning11. ML Terminology12. Machine Learning Data13. Data Clusters14. Linear Regressions15. Deep Learning (DL)16. Brain.js

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Machine Learning (ML)Neural Networks (NN)PerceptronsNeural NetworksDeep Neural NetworksDeep Learning (DL)