This is a short cheat sheet on the available parameters for regular expressions.
Cheat sheet on some of the available parameters for regular expressions
Cheat sheet for some special characters on a Mac
Cheat Sheet: Most of the Mac users know the challenge: "Finding a special character on a Mac keyboard isn't easy on a Mac sometimes."
How to create a model container image for Watson NLP for Embed
This longer blog post shows how to : … build a model init container with a custom model for Watson NLP for Embed. … upload the model init container to the IBM Cloud container registry. … deploy the model init container and the Watson NLP runtime to an IBM Cloud Kubernetes Cluster. … test Watson NLP runtime with the loaded model using the REST API.
Assign read/write permission to all users for unzipped custom model files and folders
This is a short blog post about assigning read/write permissions for all users to the unpacked "custom model files and folders".
Watson NLP for Embed customize a classification model and use it on your local machine
This blog post is about, how to customize a classification model for Watson NLP for Embed and use it on your local machine.
Run Watson Speech to Text for Embed on an IBM Cloud Kubernetes cluster in a Virtual Private Cloud environment
This blog post is about to deploy the IBM Watson Speech to Text Library for Embed to an IBM Cloud Kubernetes cluster. IBM Cloud Kubernetes cluster is a “certified, managed Kubernetes solution, built for creating a cluster of compute hosts to deploy and manage containerized apps on IBM Cloud“.
Get started with Jekyll for blog posts and deploy the blog to GitHub pages
In this blog post, we’ll take a look at Jekyll to get a basic understanding how usage and setup works. We won’t use an existing template, we’ll follow the initial steps for implementation and then we configure the source code for a custom deployment to GitHub pages.
Find simple tutorials for `Watson Libraries for Embed`
This short blog post is about where you can find great simple tutorials for "Watson Libraries for Embed".
Create a custom dictionary model for Watson NLP
This blog post is about, how to create a custom dictionary model for Watson NLP. One capability of the Watson NLP is the "Entity extraction to find mentions of entities (like person, organization, or date)." We will adapt the Watson NLP model to extract entities from a given text to find single entities like names and locations which are identified by an entry and its label.
Run Watson NLP for Embed in a KServe ModelMesh Serving environment on an IBM Cloud Kubernetes cluster in a VPC environment
This blog post is about to run Watson NLP for Embed example in a KServe ModelMesh Serving environment on an IBM Cloud Kubernetes cluster in a Virtual Private Cloud environment and reuses parts of the IBM Watson Libraries for Embed documentation.
Thomas Suedbroecker's Blog 