Artificial Intelligence vs Machine Learning vs Deep Learning

Source: Deep Learning on Medium

Artificial Intelligence vs Machine Learning vs Deep Learning

An example of artificial intelligence in today’s world is the amazon echo. This is one of the examples of artificial intelligence we are using today as a commercial deployment.

The example of machine learning is the google search engine. The algorithms in the google search engine will be guessing the pages we like and that we don’t like and retrieve the information accordingly.

We have an example of deep learning where we have a greyscale image that comes into a neural network and we get the output as a colored image. The black and white image goes into the neural network. The neural network has looked at all the different pictures on the web or where it takes in the data from as input. Then the neural network is able to identify the features in the input image and color the output image.

Humans are able to use the available information to make decisions to communicate with other people, identify patterns, remembering things and many more. Whereas artificial intelligence is the development of the computer system which completes a task that requires human intelligence providing more accurate results.

The way the machine learning works is that we have labeled data with features. The algorithm will learn the features in the input image and label the output images. Here the system is able to make decisions based on past data. In deep learning, we take a large unlabeled dataset and we train them using artificial neural networks. Using backpropagation the neural networks learn about the input data. After training, if we put new data in for testing the model will predict the output label accordingly. In deep learning, performance improves with more data.

Advantages of Machine learning:

  1. Powerful processing capability.
  2. Quick and accurate outcomes.
  3. Can analyze very large amounts of data
  4. Inexpensive.

The more affordable way to move into the future is to apply machine learning in business problems.

Advantages of Deep Learning:

  1. Better Scalability
  2. Problem solved in the end-to-end method
  3. Lesser testing time
Deep learning is a subset of Machine Learning.

Examples of Artificial Intelligence:

  1. News Generation
  2. Amazon Echo

Examples of Machine Learning:

  1. Spam Detection
  2. Google Search Engine

Examples of Deep Learning:

  1. Chat Bots
  2. Image classification and reconstruction.