- In his recent blog post ” Fizz Buzz in TensorFlow ,” Grus imagines he’s asked to solve Fizz Buzz as part of a job interview.
- With Fizz Buzz, you print the numbers from 1 to 100, except if it is divisible by 3, you print “fizz”; if it’s divisible by 5, you print “buzz”; and if it’s divisible by 15 you print “fizzbuzz.”
- If you’ve ever learned to program, you’ve probably written a Fizz Buzz test.
- Because Grus is building a multi-layer perceptron – a neural network – to let the computer learn from the training data set (the actual Fizz Buzz results) and let it predict whether you’ll get Fizz or Buzz for each number.
- Check out the full post for details on how Grus builds a simple neural network with TensorFlow to predict FizzBuzz numbers.
Read the full article, click here.
@googlecloud: “Sure, you’ve probably written a Fizz Buzz test. But can you do it in @TensorFlo? Learn how:”
The blog post Fizz Buzz in TensorFlow by Joel Grus raised buzz by imagining a machine learning solution to Fizz Buzz.
The (fizz) buzz around TensorFlow and machine learning