Machine learning models use algorithmic processes to learn the trends and underlying patterns found within a dataset to make predictions based on new inputs.
Automated machine learning platforms are deployed to help businesses gain insights from consumer behavior and industry trends. This knowledge can then be used to help leaders make data-driven decisions that can help their business grow.
For example, an algorithmic machine learning model can predict which outcome is likely to occur for your target variable based on the training data that was used. They identify relationships and patterns that can then be used to analyze similar data obtained in the future.
There are two main categories of machine learning methods: supervised and unsupervised learning.
With supervised learning methods, the goal is to find what leads to an outcome for a specific target. This type of learning includes classification models, which aim to predict how likely a new data point is to fall into a particular category. Regression models are another form of supervised learning, and these always have a numerical target.
On the other hand, unsupervised learning does not have a target that it must find. Instead, the model will form groups within the dataset or make observations about what is similar – often requiring further interpretation. Unsupervised learning models include clustering and dimension reduction.
Machine learning models allow businesses to analyze data on a large scale through the use of automated processing. It can help them determine the relationship between target variables and the selected features, as well as uncover relationships that can help drive decision making.
Consider how easy it is to turn on Netflix and have the program automatically recommend shows that you will like – this is possible because of machine learning models! Their models have analyzed your behavior – in this case, your watch history – and have applied what they know about trends to suggest similar content.
This type of user-specific targeting has paved the way for business improvement and shows the value that automated machine learning platforms can provide.
It doesn’t matter if you only have BI analysts, IT leaders, or executives wanting to leverage machine learning models or if you have a team of in-house data scientists looking to be more impactful with their analytic output. Any organization looking to start or advance their AI journey can benefit from machine learning models.
At LogicPlum, we understand the importance of using data to drive strategic decisions. We give you access to some of the most sophisticated automated machine learning platforms in the industry, allowing you to produce an array of machine learning models with the click of a button – no data scientists needed!
We provide model blueprints and tools for feature engineering to ensure that not only is your machine learning model useful, but also that it is interpretable once it is deployed.
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