talos | Talos is a modern OS for Kubernetes | Continuous Deployment library

I have a Linux system where the disk space shows as only 29Gb, but when I look at the partition with the parted - print command it shows as a 64Gb partition. I'm not sure if the remaining disk space is unallocated, mounted in other folders, stuck in "tmpfs" or how to add it to the primary partition. This is in Ubuntu 18.04 OS. I would like for the full 64 GB to be available at root. I appreciate any help!

When I run df -h, here are the results:

For training my neural network model I use Keras' EarlyStopping callback to minimize train time (via talos.utils.early_stopper wrapper):

I have a project in spring boot using java. I am using Spring boot 2.1.4. I implemented third party devices and call their APIs by using REST. I stored response in elastic search. I am using elastic search 7.3.
I have one API which fetch data from elastic search and front end will call this API and render data which is basically JSON data from third party API. Now I want to build one API that can return search result. For example somebody typing ip in search box then I have to find ip from JSON data not from elastic search and return result to front end.
I know that how to search data from elastic but I already fetched data and it rendered. It's another API to search data, I want to search data from rendered data. So it's a basically keyword search from JSON data by using java. I researched a lot but couldn't find anything relatable.

I want to run conform as part of my pipeline to check commit messages, but the container image lacks a shell, and has entrypoint /conform and argument enforce. My .gitlab-ci.yml should look like:

I'm using Talos and Google colab TPU to run hyperparameter tuning of a Keras model. Note that I'm using Tensorflow 1.15.0 and Keras 2.2.4-tf.

I've a corpus and I divided it into 3 parts.

1. Training set 80%
2. Dev set 10%
3. Testing set 10%

I've the below CNN model trained on Training set and Evaluated against Dev set