Dec 25, 2021

### Advent of Code 2021 in pure TensorFlow - day 6

The day 6 challenge has been the first one that obliged me to completely redesign for part 2 the solution I developed for part 1. For this reason, in this article, we'll see two different approaches to the problem. The former will be computationally inefficient but will completely model the problem, hence it will be easy to understand. The latter, instead, will be completely different and it will focus on the puzzle goal instead of the complete modeling.
Dec 22, 2021

### Advent of Code 2021 in pure TensorFlow - day 5

The day 5 challenge is easily solvable in pure TensorFlow thanks to its support for various distance functions and the power of the tf.math package. The problem only requires some basic math knowledge to be completely solved - and a little bit of computer vision experience doesn't hurt.
Dec 17, 2021

### 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.
Dec 14, 2021

### 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.