7 steps of ML Flashcards
1
Q
1 Gather the data
A
Features:
Color(nm) Alchol(%) beer/whine?
2
Q
2 Prepare the data
A
Graph How many of each What are the dangers? Training and evaluation 80% 20%
3
Q
3 Choosing a model
A
Based on the features
4
Q
4 Train the model
A
Use data to improve it Like a student learning to drive formula for straight line y = m * x + b x = input m = slope(Weight) y = output b = y-intercept biases
5
Q
5 Evaluate the model
A
Evaluation data-> Model[w, b] -> Prediction-> test ->
6
Q
6 Tune parameters
A
Parameter tuning
Training data -> Model -> Predictions
Hyper parameters
7
Q
7 Get predictions
A
What are the outcomes?
