Notes from auditing week 1 materials¶
Insights¶
In traditional programming, a programmer has to formulate or code rules manually, whereas, in Machine Learning, the algorithm automatically formulates the rules from the data.
The Traditional Programming Paradigm
The Machine Learning Paradigm
Coding the "Hello World" of Deep Learning with Neural Networks in Tensorflow¶
to figure out the relati onship between x and y, given a training set with a small number of data points.
import tensorflow as tf
import numpy as np
from tensorflow import keras
print(tf.__version__)
## Build a simple Sequential model
model = tf.keras.Sequential([keras.layers.Dense(units=1, input_shape=[1])])
## Compile the model
model.compile(optimizer='sgd', loss='mean_squared_error')
## Declare model inputs and outputs for training
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)
## Train the model
model.fit(xs, ys, epochs=500)
## Make a prediction
print(model.predict([10.0]))