Difference between revisions of "Forecasting"

Revision as of 08:08, 12 September 2020

Introduction to Forecasting in Machine Learning and Deep Learning Forecasts are critical in many fields, including finance, manufacturing, and meteorology. At Uber, probabilistic time series forecasting is essential for marketplace optimization, accurate hardware capacity predictions, marketing spend allocations, and real-time system outage detection across millions of metrics. In this talk, Franziska Bell provides an overview of classical, machine learning and deep learning forecasting approaches. In addition fundamental forecasting best practices will be covered. This video was recorded at QCon.ai 2018: http://bit.ly/2piRtLl If you are a software engineer that wants to learn more about machine learning check our dedicated introductory guide http://bit.ly/2HPyuzY . For more awesome presentations on innovator and early adopter, topics check InfoQ’s selection of talks from conferences worldwide http://bit.ly/2tm9loz

Predicting with a Neural Network explained In this video, we explain the concept of using an artificial neural network to predict on new data. We also show how to predict in code with Keras.

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+</b><br>In this video, we explain the concept of using an artificial neural network to predict on new data. We also show how to predict in code with [[Keras]].
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