Getting started with TensorFlow
An introduction to TensorFlow and Machine Learning. The presentation originally used for the TIDx event 2018
@tidxconference
6. Machine Learning Pseudocode
labeled_data = ... // f.e. X: square_meters -> y: house_prices
model = ... // f.e. y = B * x + A
// Training
do N times: // epochs
for d in labeled_data: // usually in batches
y_predicted = model.predict(d)
model.adjust(y_predicted - y, learning_rate)
// Inference
model.predict(unseen_data)
19. Real world TensorFlow
1. Find a model to the type of problem you want to solve
2. Obtain as much good data as possible
3. Train the model (or retrain)
4. Save the model and deploy it