Python for LSTMs, ARIMA, Deep Learning, AI, Support Vector Regression, +More Applied to Time Series Forecasting
Instructed by Lazy Programmer 23.5 hours on-demand video
After completing the course, you will…
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ETS and Exponential Smoothing Models
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Holt’s Linear Trend Model and Holt-Winters
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Autoregressive and Moving Average Models (ARIMA)
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Seasonal ARIMA (SARIMA), and SARIMAX
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Auto ARIMA
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The statsmodels Python library
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The pmdarima Python library
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Machine learning for time series forecasting
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Deep learning (ANNs, CNNs, RNNs, and LSTMs) for time series forecasting
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Tensorflow 2 for predicting stock prices and returns
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Vector autoregression (VAR) and vector moving average (VMA) models (VARMA)
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AWS Forecast (Amazon’s time series forecasting service)
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FB Prophet (Facebook’s time series library)
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Modeling and forecasting financial time series
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GARCH (volatility modeling)
Who this course is for:
- Anyone who loves or wants to learn about time series analysis
- Students and professionals who want to advance their career in finance, time series analysis, or data science
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Deal Score-7
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