Attendees gained a comprehensive understanding of the how to prepare data for AI opportunities and appreciated the difference between training and test data. They also received valuable insights into the risk and ethical considerations crucial for their businesses as well as when to call in AI modelling experts.
Here’s what attendees had to say …
- “A perfect learning opportunity to bring AI into our business”,
- “It was great to discover low/no code options”,
- “I learnt which machine learning types would work best for my business”,
- “Amazed that Azure runs over 50 AI models out of the box!”
Key Takeaways
Data Tools
You can use the following data tools to set up an AI model, Microsoft Azure, H2O.ai, Alteryx, AWS, IBM, Databricks, and Google Cloud. Typically, we use Azure, as we’re Microsoft Partners and Azure integrates seamlessly with other Microsoft tools like Power BI.
In the demonstration, we used Microsoft Azure Machine Learning (ML) to showcase how to set up a time series forecasting model. The model utilises historical sales data to predict future sales for the upcoming year.
“It was a very eye-opening presentation”
Keith Hunter, FM Manager at Munday and Cramer
Machine Learning Options
There are five primary categories of Machine Learning that address most problems:
Examples of when to use each machine learning category…
- Classification: Useful for assigning vertical markets to new clients for targeted advertising.
- Natural Language Processing (NLP): Employed for email bots, sentiment analysis, and language models like GPT.
- Time Series: Enables forecasting trends and making predictions based on historical data.
- Regression: Applied to understand the relationship between variables, such as ice cream sales figures alongside weather data.
- Computer Vision: Used for analysing and interpreting visual data, for example product identification.
Interested in discussing AI opportunities?
Call us +44 (0) 1245 955 633 or email us [email protected] to schedule a custom AI / machine learning session for your business or to find out about upcoming events.