Introduction to Deep Learning Day 1

1.1 Welcome

• AI is the new Electricity.

• Electricity had once transformed countless industries: transportation, manufacturing, healthcare, communications, and more.

• AI will now bring about an equally big transformation.

1.2 What you’ll learn

Courses in this sequence (Specialization):

1 Neural Networks and Deep Learning

2 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

3 Structuring your Machine Learning project

4 Convolutional Neural Networks

5 Natural Language Processing: Building sequence models

1.3 What is a Neural Network?

Basic intuitions

The term deep learning refers to training neural networks.

Example 1 – Single neural network

Example 2 – Multiple neural network

If you think of this neuron is being like a single Logo brick, you then get a bigger neural network by stacking together many of these Lego bricks.

By stacking together a few of the single neurons, we now have a slightly larger neuro network.

Part of the magic of a neural network is that when you implement it you need to give it just the input - x and the output y, for the number of examples in your training set and all these things in the middle it will figure out by itself.

Hidden units in a neural network that each of them takes its input of four input features.

And the remarkable thing about neural networks is that given enough data about x and y, given enough training examples with both x and y, neural networks are remarkably good at figuring out functions that accurately map from x to y.

Summary 

Neural networks

Single neural network

Multiple neural network

Housing Price Prediction

Function ReLU

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