What is Machine Learning (With Video and Interview Questions)

To See All ML Articles: Index of Machine Learning

Intro to Machine Learning (ML Zero to Hero - Part 1)
By: TensorFlow



Machine Learning Foundations: Ep #1 - What is ML?
By: Google for Developers



Interview Questions

Q1: What does this model seem to represent?

a. Coding
b. Machine Learning



Q2: Can you draw a similar model for Machine Learning?

Q3: Take a look at these numbers:

X = -1,  0, 1, 2, 3, 4
Y = -3, -1, 1, 3, 5, 7

What kind of model would you use for this data for best results?

Q4: Why and how is Laurence able to use Neural Network for this data from Q3?

Q5: What kind of problem is this from Q3? Is it Regression, Clustering or Classification?

Q6: What is the role of an optimizer in training a Neural Network?

Q7: What would be the output of this code?
Assuming all the imports are there.


model = keras.Sequential([keras.layers.Dense (units=1, input_shape=[1])]) 
model.compile(optimizer='sgd', loss='mean_squared_error')
xs = np.array([-1.0, 0.0, 1.0, 2.0, 3.0, 4.0], dtype=float) 
ys = np.array([-3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)
model.fit(xs, ys, epochs=500)
print(model.predict([10.0]))

Q8: Would the answer to Q7 be exactly 19 or roughly 19? Explain why.

Tags: Machine Learning,Video