In machine learning, time series analysis and forecasting are of fundamental importance in various practical fields. In this article, I will take you through 10 Machine Learning projects on Time Series Forecasting solved and explained with Python programming language.
Machine Learning Projects on Time Series Forecasting
- Covid-19 Cases Predictions for Next 30 Days
- Stock Price Prediction using Linear Regression
- Earthquake Prediction Model
- Predict Migration
- Weather Prediction Model
- Time Series with LSTM
- Daily Births Forecasting
- Google Stock Price Prediction
- Anomaly Detection using ARIMA Model
- Rainfall Prediction Model
What is Time Series Analysis?
A time series is a series of observations, observed over a period of time. In general, observations can be over an entire interval, sampled randomly over an interval or at fixed times.
In many situations, when we look at time series, regressors are also available. Regressors can be an exogenous variable, but they can even be time (or functions of time) because, for a time series, the index t has a significant order and can be treated as a regressor.
Often, data is assumed to be generated using a parametric model. By parametric model we mean a model in which all parameters except a finite number are assumed to be known. The simplest model is probably the linear model.
Different types of time sampling require different approaches to time series analysis which you will learn in the projects mentioned above.
Hope you liked this article on 10 projects on time series forecasting solved and explained with Python programming language. Please feel free to ask your valuable questions in the comments section below.