In Data Science, when we are working on a problem whose output depends on periods or intervals, it means that we are working on a problem based on a time series analysis. If you want to work on some data science projects on time series analysis, this article is for you. In this article, I’m going to introduce you to some of the best data science projects on time series analysis that you can try.
Data Science Projects on Time Series
Currency Exchange Rate Prediction:
Currency exchange is one of the biggest financial markets. Currently, 1 US dollar is equivalent to 74.72 Indian rupees. Many factors affect exchange rates such as economic, political and even psychological factors. Predicting the exchange rate is a difficult problem. There are many machine learning algorithms that we can use to predict future exchange rates. You can also use artificial neural networks for this task. In this data science project on time series analysis, I will take you through the task of predicting the exchange rate using the Python programming language. You can find this project here.
Covid-19 Cases Prediction:
In this data science project on time series analysis, you need to predict the cases of covid-19 for the next few days. Such types of predictive modelling help provide an accurate prediction of epidemics, which is essential for gaining insight into the spread and consequences of infectious diseases. The government and various legislative bodies always rely on this type of analysis to suggest new policies and assess the effectiveness of policies already in place. You can find this project solved and explained using Python from here.
Summary
So these were some of the best projects on time series analysis that you can try. In Data Science, when we are working on a problem whose output depends on periods or intervals, it means that we are working on a problem based on a time series analysis. I hope you liked this article on data science projects on time series analysis. Feel free to ask your valuable questions in the comments section below.
