Neural Networks freeCodeCamp

• Why are neural networks often called black boxes?

  They are automatically generated from data
• What does Dr. Ru believe is valuable in learning?

  Revisiting basics from time to time
• What is the final challenge in the course?

  Teach the car how to race
• What algorithm will students learn to implement for navigation?

  Dijkstra's shortest path algorithm
• What will students learn about the car's perspective?

  How to code the camera sensor
• What will students learn to enhance the car's control?

  Implement analog steering
• What is the purpose of the new camera sensor?

  To render what the car sees
• How does Dr. Ru describe AI in the course?

  As a combination of various technologies
• What is the difference between AI and machine learning?

  AI is broader than machine learning
• What is necessary for adding machine learning to the system?

  Data is required
• What does the right-hand rule help the car do?

  Navigate through mazes
• What happens when the manual override is activated?

  The car is controlled by keyboard keys
• How do the proximity sensors function?

  They detect nearby objects and their distance
• What indicates the proximity sensor's reading?

  It lights up when close to an object
• What color indicates positive values in the speed sensor?

  Yellow
• What color indicates negative values in the speed sensor?

  Blue
• What happens when the car's speed sensor reads negative values?

  The car is moving backwards
• How does the neural network decide to move the car?

  Based on input values and weights
• What must happen for a neuron to light up in the network?

  Input value times weight must exceed bias
• What happens if the bias is set to zero in the neural network?

  The neuron cannot light up
• What is the effect of lowering the bias in the neural network?

  The neuron can light up
• What happens when the weight is set to a negative value?

  The neuron can turn off
• What is the significance of the sweet spot in the neural network?

  It determines when the neuron activates
• What should students do to modify the car's behavior?

  Adjust weights and biases in the network
• What is the purpose of the manual override button?

  To control the car with keyboard keys
• How does the car's performance compare to manual control?

  The car performs better than manual control
• What happens when the car crashes during simulation?

  The simulation can be restarted
• What is the first input to the neural network in the simpler scenario?

  The front-facing sensor
• How many neurons are in the simpler neural network?

  One neuron
• What decision can the simpler neural network make?

  To go forward or not
• Why does the simpler neural network not light up?

  Its weight is set to zero
• What must be done to make the simpler neural network activate?

  Lower the bias to a negative value
• What happens when the weight is set to a negative value in the simpler network?

  The neuron can turn off
• What is the effect of modifying the weight in the simpler neural network?

  It changes the car's ability to move
• What is the relationship between input value and weight in the neural network?

  Input value is multiplied by weight
• What happens when the bias is set to a positive value in the simpler network?

  The neuron cannot activate
• What is the significance of the bias in the neural network?

  It determines neuron activation threshold
• How does the car's behavior change with different weight values?

  It affects the car's movement decisions
• What is the role of the manual override in the simulation?

  To allow manual control of the car
• What happens when the car's input values change?

  The car's movement decisions may change