I hope to use IBM speech recognition service without – curl or ibm_watson module. And my attempt is below: Even though, I have ‘Service credentials’ for IBM cloud – speech to text, I cannot find correct form for the function. In the documents of recognize_ibm(), it is said that I need to enter the link_1 to find my username in
Tag: ibm-cloud
ModuleNotFoundError for ibm-watson-machine-learning package
I entered following command in my jupyter notebook: !pip install -U ibm-watson-machine-learning and with I can see the package install with !pip list. But when I try to import like so: import ibm_watson_machine_learning, I get following error: ModuleNotFoundError: No module named ‘ibm_watson_machine_learning’. Answer SOLVED: For me, I simply needed to update all my packages in conda with conda upgrade –all.
IBM Cloud Functions – “Invalid virtualenv. Zip file does not include activate_this.py”
I want to deploy a python script with a virtual environment (I need a library which is not in the runtime provided by IBM Cloud Functions) to IBM Cloud Functions. I want to do this with simple zipping so I followed the documentation: Packaging Python code with a local virtual environment in a compressed file in the link below: https://cloud.ibm.com/docs/openwhisk?topic=openwhisk-prep
IBM Watson CPLEX Shows no Variables, no Solution when solving LP file
I’m migrating an application that formerly ran on IBM’s DoCloud to their new API based off of Watson. Since our application doesn’t have data formatted in CSV nor a separation between the model and data layers it seemed simpler to upload an LP file along with a model file that reads the LP file and solves it. I can upload
URL for IBM Cloud Kubernetes deployment
This is a bit of a beginner’s question. I’m attempting to get a simple Hello World Python flask application deployed in a kubernetes cluster on IBM Cloud. The application (main.py): I build my Docker image with docker build –rm -t kube-hw . and Dockerfile: I run it locally with docker run –rm -p 5000:5000 kube-hw. That works fine. I can