Deep Learning Analyst Paper

Secrets for Successful Deep Learning Projects

How to get from idea to insight

We’ve heard it all. Computers are able to work longer, don’t get tired, don’t make errors, and continue to do the same thing over and over without complaint. Machine learning is revolutionizing every industry on the planet. But a problem persists: How do you go from an idea in your head that might have merit to getting a computer to work on it for you?


EnterpriseTech explains how you can apply machine learning and deep learning to your own problem-solving. They examine the use case of speeding up weather insight with Nowcasting — a process that uses deep learning models trained using historical data. Nowcasting fills the gap between current observations and forecasts derived using standard numerical weather prediction (NWP) techniques.

Download this paper to learn about:

What types of
problems are good
candidates for machine
learning

The biggest mistake
made with new
machine learning
projects

How to get started
today on your own
machine learning
journey

Find out the differences between commonly used terms:

  • Machine learning
  • Deep learning
  • Deep neural network
  • Supervised vs. unsupervised learning

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