Time Series Analysis, Forecasting, and Machine Learning

<div>Welcome to Time Series Analysis, Forecasting, and Machine Learning in Python.&nbsp;<span style="font-size: 1rem;">Time Series Analysis has become an especially important field in recent years.&nbsp;</span><span style="font-size: 1rem;">With inflation on the rise, many are turning to the stock market and cryptocurrencies in order to ensure their savings do not lose their value.&nbsp;</span><span style="font-size: 1rem;">COVID-19 has shown us how forecasting is an essential tool for driving public health decisions.&nbsp;</span><span style="font-size: 1rem;">Businesses are becoming increasingly efficient, forecasting inventory and operational needs ahead of time.</span></div><div><br></div><div><span style="font-size: 1rem;">Let me cut to the chase. This is not your average Time Series Analysis course. This course covers modern developments such as deep learning, time series classification (which can drive user insights from smartphone data, or read your thoughts from electrical activity in the brain), and more.</span></div><div><br></div><div>We will cover techniques such as:</div><div><ul><li>ETS and Exponential Smoothing</li><li><span style="font-size: 1rem;">Holt's Linear Trend Model</span></li><li><span style="font-size: 1rem;">Holt-Winters Model</span></li><li><span style="font-size: 1rem;">ARIMA, SARIMA, SARIMAX, and Auto ARIMA</span></li><li><span style="font-size: 1rem;">ACF and PACF</span></li><li><span style="font-size: 1rem;">Vector Autoregression and Moving Average Models (VAR, VMA, VARMA)</span></li><li><span style="font-size: 1rem;">Machine Learning Models (including Logistic Regression, Support Vector Machines, and Random Forests)</span></li><li><span style="font-size: 1rem;">Deep Learning Models (Artificial Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks)</span></li><li><span style="font-size: 1rem;">GRUs and LSTMs for Time Series Forecasting</span></li></ul></div><div><span style="font-size: 1rem;">We will cover applications such as:</span></div><div><ul><li>Time series forecasting of sales data</li><li><span style="font-size: 1rem;">Time series forecasting of stock prices and stock returns</span></li><li><span style="font-size: 1rem;">Time series classification of smartphone data to predict user behavior</span></li><li><span style="font-size: 1rem;">The VIP version of the course will cover even more exciting topics, such as:</span></li><li><span style="font-size: 1rem;">AWS Forecast (Amazon's state-of-the-art low-code forecasting API)</span></li><li><span style="font-size: 1rem;">GARCH (financial volatility modeling)</span></li><li><span style="font-size: 1rem;">FB Prophet (Facebook's time series library)</span></li></ul></div><div><span style="font-size: 1rem;">So what are you waiting for? Signup now to get lifetime access, a certificate of completion you can show off on your LinkedIn profile, and the skills to use the latest time series analysis techniques that you cannot learn anywhere else.</span></div><div><br></div><div>Thanks for reading, and I'll see you in class!</div><div><br></div><div>UNIQUE FEATURES</div><div><ul><li>Every line of code explained in detail - email me any time if you disagree</li><li><span style="font-size: 1rem;">No wasted time "typing" on the keyboard like other courses - let's be honest, nobody can really write code worth learning about in just 20 minutes from scratch</span></li><li><span style="font-size: 1rem;">Not afraid of university-level math - get important details about algorithms that other courses leave out</span></li></ul></div>

What you'll learn:

• ETS and Exponential Smoothing Models
• Holt's Linear Trend Model and Holt-Winters
• Autoregressive and Moving Average Models (ARIMA)
• Seasonal ARIMA (SARIMA), and SARIMAX
• Auto ARIMA
• The statsmodels Python library
• The pmdarima Python library
• Machine learning for time series forecasting
• Deep learning (ANNs, CNNs, RNNs, and LSTMs) for time series forecasting
• Tensorflow 2 for predicting stock prices and returns
• Vector autoregression (VAR) and vector moving average (VMA) models (VARMA)
• AWS Forecast (Amazon's time series forecasting service)
• FB Prophet (Facebook's time series library)
• Modeling and forecasting financial time series
• GARCH (volatility modeling)