Azure Machine Learning – Predicting Fashion Trends

After doing some research on Azure Machine Learning and how it works, I thought to myself how could this be applied to my own interests. The first thing that came to mind was fashion! It seemed amazing that I could predict fashion trends before they even arose. Now this does come with a certain level of uncertainty and would need some pre requisites but stay with me.

First thing you’re probably asking is “”What is Machine Learning?”. Machine learning (in short) is a process used to predict outcomes based on historic data. We can use this data to create our own model, parameterise it and start passing in our own data. We need to first ensure that our source dataset is rich and by this I mean it needs to have tags like: Clothing Type, Date, Sales etc. We can use this to predict what an item could sell for in the future and if there has been much demand for an item somewhere in the future.

The next thing would be to pass in our own data to find out if an item of clothing will be popular in the future. E.g. if we have a new brand of hoodie and we pass through tags present in the data set we should be able to predict how popular this could be with a level of uncertainty. It’s key I mention this as machine learning isn’t something that gives you a black and white answer! It will give us an answer which is most likely to occur based on the other outcomes.

So you may think that “I don’t need to use machine learning” well you may think that now but once your competitors start using it to gain more sales, they need to come from somewhere and they’ll likely be your customers. What’s good to know though is you can start today using Azure Machine Learning. This is Microsoft’s answer to machine learning as a whole and is a great way to start. Even better, you can start for free!

To get access to Azure Machine Learning please follow the below link:
https://azure.microsoft.com/en-gb/free/services/machine-learning/?&OCID=AID719823_SEM_qdA5m1pn&lnkd=Bing_Azure_Brand&dclid=CJD2sq3_kN8CFUmiUQoddj8I-Q

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