From the course: Deep Learning: Getting Started
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An analogy for deep learning
From the course: Deep Learning: Getting Started
An analogy for deep learning
- [Instructor] Let's use an analogy to understand how deep learning works. We will use this analogy later in the course. Deep learning is a complex and iterative process that requires a series of trials to narrow down the parameters for the model. It starts actually with random initialization of the model parameters and works towards the right values of these parameters by trial and error. In the case of a linear regression model, the model parameters are A and B. The values of A and B form the model that determines the relationship between X and Y. For analogy, let's try to find the values of A and B in the formula, 10 = 3A + B. We will follow a similar trial and error process to narrow down these values. Let's start the trials. We will initialize the values of A and B to a random value. In this case, we initialize both to 1. We then compute the value of Y using the formula, 3A + B. The result is 4. The expected result is 10, though. We end up with an error of 6. Now, we will use…
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