Unleash Insights from Time Series Data
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Are you ready to unravel the mysteries hidden within time series data? Look no further than the Time Series Guide! Repository is packed with resources, project ideas, and tips to help you master the art of time series analysis 📈 Join us on a journey of exploration and discovery, and unleash the power of time series in your data science journey! 🚀
🟣 Why Time Series Analysis ?
Have you ever wondered what the stock market will look like next month? Or how the weather will be next week? Or what will be the sales of the store in next quarter ❓ These questions are perfect examples of the kind of problems that can be solved with the help of time series analysis. Time series analysis allows you to understand, interpret, and predict patterns in data over time. By analyzing past trends and patterns, we can gain insights into what the future may hold with the perspective of data. So get you're ready to unlock the secrets of time series analysis 📊
🟣 Difference between Time Series and Interpolation Method ?
Major difference between time series analysis and interpolation methods is that time series analysis is focused more on analyzing data over time to identify patterns, and trends. While interpolation methods are focused on estimating missing data points between known data points.
Time series analysis ----> When predicting future values is important
Interpolation methods ----> Filling in missing data.
👨💻 Provides a step by step guide to exploratory data analysis and forcasting modelling for time series.
📚 Repository contains a list of resources such as tutorials, courses, books, articles, and videos to deepen their knowledge of time series analysis.
⭐ Offers project ideas that users can work on to apply their knowledge of time series analysis.
🤝 Encourages collaborative learning and sharing of knowledge among others.
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Sales forecasting
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Stock market forecasting
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Weather forecasting
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Disease outbreak forecasting
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Traffic forecasting
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Energy demand forecasting
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Website traffic forecasting
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Supply chain forecasting
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Predicting social trends, for an example fashion and food which will be helpful for industry to understand and adapt according to it.
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Wildlife population forecasting, to predict wildlife populations based on historical data which is helpful to take the action at correct time.
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Forecasting: Principles and Practice (Textbook)
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Time Series Cheatsheet (Cheatsheet)
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Machine learning for trading (Udacity-Course)
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Time Series with Python (Datacamp-course)
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11 Classical Time Series Forecasting Methods in Python (Cheatsheet)
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Forecasting Future Prices of Cryptocurrency using Historical Data (Blog)
For more course reasources, I have created a separate thread:
https://www.kaggle.com/discussions/general/310100#1706540
If you have any feedback, please reach out to us at hrishikesh3321@gmail.com