Cubist | Python package for fitting Quinlan | Analytics library

I tried to follow the examples in the

Link 1 - Sparse Matrix https://www.tidyverse.org/blog/2020/11/tidymodels-sparse-support/

Link 2 - Workflow_sets https://www.tmwr.org/workflow-sets.html

I had trouble including the blue print into the workflow sets.

In the examples where workflow_set is defined in link 2

I'm trying to view how this model performs against prior actual close. I'm using a workflow_set model and have no issues extracting the forecast. I've supplied a reproducible example below. I'd like to be able to plot actual, with a backtested trend line along with the forecast.

I could and should have made a simpler reprex, but this is really straight out of my work. After training a C5.0 model in the Tidymodels framwork, how do I "see" the rules that the model generated? I tried to replicate what is illustrated here

https://www.tidyverse.org/blog/2020/05/rules-0-0-1/

but I did not go very far (but I am sure the solution must be a one-liner).

Many thanks!

I am currently trying to learn to use Google Kubernetes Engine and Google Cloud SQL. In doing so i have created a AspnetCore 3.1 Web Api project in my visual studio 2019, to use as a training project.

At the moments i am currently able to do the following.

• Deploy the Web Api to GKE, using Google Cloud Tools for Visual Studio
• Connect to Cloud SQL from own PC, using SSMS and Cloud SQL Proxy

What i want to be able to do is as follows.

• Deploy the Web Api to GKE, using Google Cloud Tools for Visual Studio, with a sidecar, containing Cloud SQL Proxy

From my understanding of Cloud SQL, it is best to always access it via the proxy, as it is more secure, which is why i want the sidecar. To get the proxy to work, i however need the credential file saved in my secrets in GKE. I also have some database related variables that need to be passed in as environment variables, again from secrets in GKE.

At the moment in my solution, beside my api project file, i have a Dockerfile, that looks as follows.

I am trying to auto scale java spring framework kafka consumer with docker-compose with --scale flag and forwarding ports in docker-compose.yaml like "8070-8072:8070". So when i trigger endpoint for publishing messages, it does well. But in consumer side just 1 consumer consumes all messages. I have 3 consumer with same group-id and different client-id. What i want is a distributed messaging. I read some paper about partitioning and i looked up my logs. It seems there just 1 partition. Is it the reason? How can i achieve this? I'll add the log, consumer config, publisher config and docker-compose file. Firstly the log. It seems just 3 of 1 have partition.

command:

I'm trying to create a table with React that will receive JSON data eventually (via HTTP request). I am currently storing the data in the state of my first component, and then rendering the table in my second component.

I would like each row in my table to contain an image of an album cover, followed by text data about the track, artist, and album title. For this post, I will include one row of my data so that you may see how it is stored in state.

I am currently unable to render an image stored as a string in state. What could I changed about my getRowsData() function in order to make this work? Or maybe I need to change how I am calling my image string? Any help or advice would be greatly appreciated.

The state (with image string as a .jpeg file) is found here: