8 - Deep Learning and Neural Networks
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What are the three main layers in a neural network?
💡 Hint: Think about how the model receives input, processes it, and outputs a result.
Name one common activation function.
💡 Hint: It helps determine the output of neurons.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does the Sigmoid function do?
💡 Hint: Remember what happens to input values in the activation function.
True or False: Dropout randomly turns off neurons during training to prevent overfitting.
💡 Hint: Think about how this method impacts learning.
Get performance evaluation
Challenge Problems
Push your limits with advanced challenges
How would you implement dropout in a neural network, and what impact would it have on model performance?
💡 Hint: Consider how random removal helps combat overfitting.
Consider a scenario where you notice the vanishing gradient problem in your deep learning model. What strategies might you employ to alleviate this issue?
💡 Hint: Think about how adjusting layers can affect gradient flow.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.