Deep Learning - Crash Course 2023 - Manual Fitting of Data

The video tutorial explains how the sigmoid function changes with parameters W and B, and demonstrates fitting data into a sigmoid neuron. It includes an exercise to manually adjust parameters to fit data, highlighting the challenges of this approach and the need for mathematical methods in deep learning applications.

What happens to the sigmoid plot when the parameter W is negative?

• The plot flips, starting from 1 and decreasing to 0.

• The plot becomes a straight line.

• The plot shifts to the right.

• The plot remains unchanged.

In the exercise, what is the main goal when fitting data into a sigmoid neuron?

• To determine the correct parameters for predicting outputs of new inputs.

• To visualize the data points in a 3D graph.

• To calculate the average of all data points.

• To find the maximum value of the sigmoid function.

What is the initial step in manually adjusting the parameters W and B?

• Choosing random values for W and B.

• Setting W and B to zero.

• Plotting the data points on a 3D graph.

• Calculating the derivative of the sigmoid function.

Why is manually adjusting parameters not feasible for complex data?

• It requires too much computational power.

• It is too time-consuming and prone to errors.

• It does not provide accurate results.

• It is only suitable for binary classification problems.