Advent of Code 2021 in pure TensorFlow - day 4
Using tensors for representing and manipulating data is very convenient. This representation allows changing shape, organizing, and applying generic transformations to the data. TensorFlow - by design - executes all the data manipulation in parallel whenever possible. The day 4 challenge is a nice showcase of how choosing the correct data representation can easily simplify a problem.
Advent of Code 2021 in pure TensorFlow - day 3
A Solution to the AoC day 3 puzzle in pure TensorFlow. This challenge allows us to explore the TensorArray data type and find their limitations when used inside a static-graph context. We'll also use a tf.function experimental (but very useful) feature for avoiding useless retraces and reusing the same graph with tensors of different shapes.
Advent of Code 2021 in pure TensorFlow - day 2
A Solution to the AoC day 2 puzzle in pure TensorFlow. How to use Enums in TensorFlow programs and the limitations of tf.Tensor used for type annotation
Advent of Code 2021 in pure TensorFlow - day 1
Solving a coding puzzle with TensorFlow doesn't mean throwing fancy machine learning stuff (without any reason) to the problem for solving it. On the contrary, I want to demonstrate the flexibility - and the limitations - of the framework, showing that TensorFlow can be used to solve any kind of problem and that the produced solutions have tons of advantages with respect to the solutions developed using any other programming languages.