Before you begin modeling and making predictions, you might ask yourself, “How much data do I need?”. Is there such a thing as too much data? We will tackle this topic in AI Simplified: Data Requirements.
The larger the dataset, the trickier it is to make sure that each and every piece of data is relevant to your particular business problem. Data is everywhere, and large datasets are challenging to process and build with without losing accuracy and time. So, what can we do to handle large amounts of data in an intelligent and efficient way?
Tom de Godoy, DataRobot CTO and Co-Founder, shares how automated machine learning provides the solution. Automated machine learning builds models by gradually adding to the sample size used in training the models, and ranks features by importance in the model while automatically dropping the irrelevant features.
Watch Tom’s video to learn the different ways automated machine learning handles large datasets:
If you’re wondering what automated machine learning is all about, watch Tom’s other AI Simplified video on that topic: AI Simplified: What is Automated Machine Learning?