Applying Deep Learning to Time Series Forecasting with Python

Applying Deep Learning to Time Series Forecasting with Python

In this project, we will use traditional time series forecasting methods as well as modern deep learning methods for time series forecasting.
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Customer Love

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Dhiraj Tandon linkedin profile url

Solution Architect-Cyber Security at ColorTokens

My Interaction was very short but left a positive impression. I enrolled and asked for a refund since I could not find the time. What happened next: They initiated Refund immediately. Their... Read More

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Nathan Elbert linkedin profile url

Senior Data Scientist at Tiger Analytics

This was great. The use of Jupyter was great. Prior to learning Python I was a self taught SQL user with advanced skills. I hold a Bachelors in Finance and have 5 years of business experience.. I... Read More

What will you learn

AR Models, MA Models
ARIMA Models
NN Models
DNN Models
RNN Models
LSTM Models

Project Description

The term "univariate time series" refers to a time series that consists of single (scalar) observations recorded sequentially over equal time increments.A common assumption in many time series techniques is that the data are stationary.​ A stationary process has the property that the mean, variance and autocorrelation structure do not change over time.​ We will use traditional time series forecasting methods as well as modern deep learning methods for time series forecasting. ​​

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Curriculum For This Mini Project