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Demand forecasting using Deep learning


July 25, 2020

Forecasting for cash vending machines can be demanding with various reasons for dips and spikes in the demand, such as weekday, weekend, location, beginning and ending of the month, and holidays. The biggest challenge is to remember the pattern of withdrawals with respect to the reasons stated previously. This is where deep learning comes into the picture, and we are referring to recurrent neural networks (RNN).

But why use deep learning for this? We need to mimic human behavior of cash withdrawals by remembering the recent past and then use what is learned to predict the future.

Come learn how to build and deploy your very own neural networks. IBM Watson Studio allows you to build and run Jupyter Notebooks within one environment making development experience seamless and easy.

Learning Outcomes

✅Design complex neural networks then experiment at scale to deploy optimized deep learning models, within Watson Studio.
✅Systems and scientific methods to analyze structured and unstructured data in order to extract knowledge and insights.
✅Analytics delivers the value of data for the enterprise.

Prerequisites & Required Installations
✔️IBM Cloud Account – Login in or Sign up at

3:00PM – 3:10PM —> On-boarding and Signups
3:10PM – 4:10PM —> Intro to TensorFlow, Keras & Spark
4:10PM – 5:00PM —> Walk-through & Questions
After the webinar the recording will be made available on Youtube:


🌟 Sidra Ahmed | IBM Cloud Developer Advocate – UAE

🌟 Fawaz Siddiqi | IBM Cloud Developer Advocate – UAE



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Dubai, United Arab Emirates