TensorFlow is a beast. It deals with machine learning algorithms, it uses Bazel to be built, it uses gRPC, etc., but let’s be honest, you are dying to play with machine learning. Come on, you know you want to! Especially in combination with Docker and Kubernetes. At Bitnami, we love apps, so we wanted to!
TensorFlow + Kubernetes + Docker + Machine learning = Awesomeness.
You just need to add bi-modal in there and you will hit buzzword bingo.
Jokes aside, TensorFlow is an open source library for machine learning. You can train data models and use those models to predict or infer information. I did not dig into TensorFlow itself, but I hear it is using some advanced neural networks techniques. NN have been around for a while, but due to computational complexity, they were not extremely useful passed a couple of layers and a couple dozen neurons (20 years ago at least 🙂 ). Once you have trained a network with some data, you can use that network (aka model) to predict results for data not used in the training data set. As a side note, I am pretty sure we will soon see a marketplace of TF models.
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