A Feature Store is useful tool to help manage Features used by Machine Learning models. I discussed in my previous blog the challenges related to Feature management, how to curate them and the desirable capabilities of a Feature Store. In this blog I will build...
There were a LOT of announcements at re:invent 2021 – nothing new in that. Standard practice in the New Year at Inawisdom is to go through a process of digesting them in a bit more depth than is possible during the hubbub of the event. As...
The use of Machine Learning has become a critical component in many businesses, examples being product recommendations, making decisions on stock levels, and evaluating credit scores. Machine Learning uses like these for businesses are having a direct impact on the top line (how money is...
Inawisdom have embedded Machine Learning models at one of our client’s business by using number of inference styles: The two most popular styles we see are real-time and batch (inc. micro). For batch, Amazon Step Functions calling a SageMaker Batch Transform are our weapons of choice....
AWS re:Invent, the annual Amazon extravaganza in Las Vegas, is on the horizon. As a technology and cloud geek I am excited to be attending for the first time in person. I found a great introductory event guide here by Mark Nunnikhoven, with useful hints...
At Inawisdom we use Serverless technologies and Micro Service architectures for embedding Machine Learning models within applications or creating distributed solutions. We have found that in production Serverless architectures are cost-efficient and address many of the classic non-functional operational and monitoring requirements of our customers. This...
By Dr. Sami Alsindi, Data Scientist at Inawisdom Time series forecasting is a common customer need, so a means to rapidly create accurate forecasting models is therefore key to many projects. Amazon Forecast accelerates this and is based on the same technology used at Amazon.com. This post explores...
At Inawisdom we are routinely taking our clients Machine Learning models and productionising them. In this blog I am going to cover some of the aspects of how we accomplish this, offer some top tips, and also share some things we’ve found along the way...
Back in September, I took part in a video shoot for the AWS “This is my architecture” series. With my host Shafreen, we discussed an AWS architecture to train an initial model in SageMaker, deploy it, continually evaluate its performance in production, and then automatically retrain the model...
What do you get when you combine 50,000 people, into one location, to talk about one subject? When that location is Las Vegas, and the subject is AWS, what else could it be other than re:Invent! Three of us have travelled the 5,000 mile, 16 hour...