UK deep tech AI company, T-DAB.AI, has closed their funding round of £495,000 to accelerate the development of their Edge AI platform.
In the second part of the supply chain analytics for business, we discuss on how tech is transforming the supply chain whilst dealing with demand volatility with predictive and prescriptive analytics
and what the future holds.
Now, more than ever, a business’s ability to react to the rapid shifts in the market is dependent on its supply chain and having visibility and insight across the entire ecosystem.
Discover how supply chain analytics can help businesses anticipate shifts in demand, proactively manage their resources, improve efficiencies and address potential risks throughout their supply chain ecosystem.
Introduction to ML Ops: How to start integrating ML solutions in your strategy
In this blog, we will discuss what pipelines are and why they are a fundamental unit against which the value of your ML investment should be measured.
Chief Data Officers recognise the importance of data in making sound business choices, but often struggle to link data to specific business advantages and outcomes.
In Part 3 of the Time-Series of Information Technology Operating Analytics article series, I have included the literature used and the current trial experiments. As I have learned a lot about different approaches to anomaly detection in time series, whilst researching for a good source that would showcase and analyze components of time-series data, I […]
In the Time-series of Information Technology Operating Analytics – Part 2 we will explore anomaly detection and the role this had on my research and future articles. Anomaly detection, also known as outlier analysis, is a branch of data mining. This technique learns from a large scale of datasets and identifies data points, events, and […]
With the time-series of information technology operating analytics blog series, I wanted to introduce you to time-series and its use in information technology operating analytics. This series of blogs describe my work on my postgraduate thesis using statistical and machine learning techniques to apply anomaly detection into Information Technology Operating Analytics (ITOA) time-series data, so that […]
Machine Learning is all about understanding data, and what can be taught under this assumption. This post introduces supervised learning vs unsupervised learning differences by taking the data side, which is often disregarded in favor of modelling considerations.