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8 PM – Advanced AI/ML – Darin
May 21 @ 8:00 pm - 9:00 pm
Today’s Activities:
- Introduced course projects, and began diving into project 1 – YOLO Live Object Classification
- Streamed videos in proper format (BGR2RGB conversion)
Homework:
When you are done, submit your file and any images into the same google drive from the intro to ML/AI!
- Watch this video: https://www.youtube.com/watch?v=aircAruvnKk
- Create a new directory in your Advanced AI PyCharm project called HW
- Create a May21_HW.py and answer the following questions:
Q1. Within a neural network, how does one layer lead to the input of a single neuron in the next layer? (hint: think about how you get the value for the input of the neuron, and its range)Q2. If the output from one layer (after aggregating all neurons) is 0.7, what is the value after using the sigmoid activation function?
Q3. Write code for implementing the sigmoid function in python using numpy. (hint: use np.exp() for the exponential function)
Finally, test your function above with input 0.7 and double check that it matches your answer from Q2. Paste a screenshot of your program working and submit to the google drive when you are finished.