Tag: Data Science

Beyond building predictive models: TwinOps in biomanufacturing

Beyond building predictive models: TwinOps in biomanufacturing

On the wave of more and more manufacturers embracing the pervasive mission to build digital twins, also biopharmaceutical industry envisions a significant paradigm shift of digitalisation towards an intelligent factory where bioprocesses continuously learn from data to optimise and control productivity. While extensive efforts are made to build and combine the best mechanistic and data-driven models, there has not been a complete digital twin application in pharma. One of the main reasons is that production deployment becomes more complex regarding the possible impact such digital technologies could have on vaccine products and ultimately on patients. To address current technical challenges and fill regulatory gaps, this paper explores some best practices for TwinOps in biomanufacturing – from experiment to GxP validation – and discusses approaches to oversight and compliance that could work with these best practices towards building bioprocess digital twins at scale.

Please read our whole pre-print here: https://doi.org/10.36227/techrxiv.16478856.v1

Senior AI/ML engineer in Bengaluru, India at GSK

Senior AI/ML engineer in Bengaluru, India at GSK

I’m hiring a Senior AI/ML engineer in Bengaluru, India. You will work with the rest of our international team on delivering cutting edge AI/ML solutions to support our vaccines business. This is a great role to grow into a lead data scientist as well as developing your machine learning and modern DevOps skills.

https://gsk.wd5.myworkdayjobs.com/GSKCareers/job/India—Karnataka—Bengaluru/Senior-AIML-Engineer_272917

Visual Object Tagging Tool and Microsoft Cognitive Toolkit

Visual Object Tagging Tool and Microsoft Cognitive Toolkit

The Visual Object Tagging Tool (VoTT) features a great bunch functionalities to kickstart your FAST-RCNN modelling using Microsoft Cognitive Toolkit (used to be called CNTK). It offers an end-to-end solution from tagging your data till deep learning model validation. After loading a bunch of images in VoTT you tag them and the tool will let you export the images in a format ready for your Microsoft Cognitive Toolkit experiment.

Visual Object Tagging Tool and CNTK

Links

VoTT on Git: https://github.com/CatalystCode/VOTT

Fast-RCNN code on Git: https://docs.microsoft.com/en-us/cognitive-toolkit/Object-Detection-using-Fast-R-CNN

 

AzureSMR: handle your Azure subscription with R

AzureSMR: handle your Azure subscription with R

Great new package for the people that use Microsoft Azure as their platform of choice and love R. With AzureSMR you are capable to handle the following services:

  • Azure Blob: List, Read and Write to Blob Services
  • Azure Resources: List, Create and Delete Azure Resource. Deploy ARM templates.
  • Azure VM: List, Start and Stop Azure VMs
  • Azure HDI: List and Scale Azure HDInsight Clusters
  • Azure Hive: Run Hive queries against a HDInsight Cluster
  • Azure Spark: List and create Spark jobs/Sessions against a HDInsight Cluster(Livy)

Install it from your interactive shell:


#Install devtools
if(!require("devtools")) install.packages("devtools")
devtools::install_github("Microsoft/AzureSMR")
library(AzureSMR)

GitHub: https://github.com/Microsoft/AzureSMR

Source: http://blog.revolutionanalytics.com/2016/12/azuresmr.html