“Practical Time Series Forecasting” by Galit Shmueli is a renowned book that skillfully guides readers through time series forecasting using R. What about those Python enthusiasts who are keen to dive into the same material? Well, we’ve got you covered!
With great pride, Analytical Ants presents our first open-source translation published on Github! We have meticulously translated the content from R to Python, walking readers through each step in an easily digestible format. Whether you’re a beginner or an experienced professional, this guide is designed to equip you with invaluable tools and insights for your data science journey.
Our guide provides comprehensive examples of #Differencing, #MovingAverages, #NaiveForecasting, #ExponentialSmoothing, #Trends, #Seasonality, #QuadraticTerms, #Autocorrelations, #Decompositions, #ARIMA, #LogisticRegression, #NeuralNets, and much more!
Your contribution is highly valued. Feel free to comment, submit PR’s for optimization, or provide feedback to make this resource even more helpful. We are confident that this tool will open new doors in your data science journey.
For all your data needs, Analytical Ants is here to assist you. Contact us for a free consultation today!
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Link: https://lnkd.in/gVpDVrb2
