Deep learning (DL) sits at the core of our company. It is what drives our platform to success and what makes our models so accurate. But why? Why should deep learning excite you more than the words machine learning, computer vision, or artificial intelligence?
In this blog series, I’ve asked the team to pull together the most important concepts of deep learning in order to better explain its benefits. We’ll first introduce you to the concept of neural networks and their importance in deep learning. Then we’ll dive into the top advantages and applications that DL has for you.
Before beginning our series, especially for our non-technical readers out there, let’s quickly define deep learning. Deep learning is a type of machine learning inspired by the connections of neurons in the brain. It uses this as an approach to teaching computer algorithms to do more complicated tasks, and it works best when you have lots and lots of data you can use to “train” the algorithm. The DL models can find complex patterns in the data, learn from them, and produce better results moving forward.
The reason we use DL at CrowdAI is simple: it produces better results more efficiently.
Deep learning also allows us to solve problems that more simplified types of machine learning wouldn’t be able to do.
Our team is constantly working to ensure that the deep learning engine that powers our platform is cutting-edge and continuously improving. We are always staying up-to-date on research on the latest DL trends so that we can pass the results of that research on to our platform users.
Now that you have a quick foundation of what deep learning is, you’re ready to explore a few important concepts of DL and its benefits.
Check back weekly for the new blogs in our Deep Learning series! We’ll link them below as they go live.
- What Are Neural Networks?
- Why Deep Learning Can Lead to More Accurate Results
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