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21 Time Series/ Forecasting Project Ideas in DL/ML

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Time series forecasting is a crucial application of machine learning and deep learning techniques. It involves predicting future values of a time series based on historical data. With the increasing availability of data and advancements in deep learning, the accuracy of time series forecasting models has significantly improved.

In this article at OpenGenus, we present a list of 21 time series/forecasting project ideas that can help you improve your skills and understanding of deep learning techniques. For each project, we provide a brief description, the dataset used, difficulty level, concepts involved, and a source code link if available on GitHub. These projects can be used to develop skills in time series forecasting and inspire you to explore further in this field.

1. Stock Price Prediction using LSTM

A project to predict the future stock price of a company using Long Short-Term Memory (LSTM) neural networks.

  • Project title: Stock Price Prediction using LSTM
  • Dataset used: Yahoo Finance
  • Difficulty level: 3
  • Concepts involved: LSTM, Time Series Forecasting
  • Source code: https://github.com/lilianweng/stock-rnn

2. Sales Forecasting with ARIMA

A project to forecast sales using the Autoregressive Integrated Moving Average (ARIMA) model.

3. Energy Demand Forecasting with RNNs

A project to forecast the demand for electricity using Recurrent Neural Networks (RNNs).

4. Time Series Anomaly Detection with LSTM

A project to detect anomalies in a time series using LSTM.

5. Bitcoin price prediction using ARIMA

A project to predict cryptocurrency prices using ARIMA.

6. Traffic Volume Prediction with LSTM

A project to predict traffic volume using LSTM.

  • Project title: Traffic Volume Prediction with LSTM
  • Dataset used: Caltrans Performance Measurement System (PeMS)
  • Difficulty level: 3
  • Concepts involved: LSTM, Time Series Forecasting, Traffic
  • Source code: https://github.com/xiaochus/TrafficFlowPrediction

7. Predicting Bike Sharing Demand

In this project, you will be predicting the demand for bike sharing using Random Forest algorithm and XGBoost.

8. Air Pollution Forecasting

Time Series Analysis of Air Pollutants(PM2.5) using LSTM model

9. Prediction of Solar Power Energy Generation

This project aims to predict solar power energy generation using machine learning models. The dataset used is from the National Renewable Energy Laboratory (NREL) and includes weather data and solar power generation data for a solar photovoltaic (PV) power plant in Alabama, USA.

10. Time Series Forecasting of Amazon Stock Prices using Neural Networks LSTM and GAN

This project implements a time series forecasting model for Amazon stock prices using Long Short-Term Memory (LSTM) and Generative Adversarial Network (GAN) models. It includes data preprocessing, model training, and evaluation of the results.

11. Cryptocurrency Price Prediction

This project aims to predict the prices of cryptocurrencies like Bitcoin and Ethereum using various machine learning and deep learning models. The project uses data from cryptocurrency exchanges to train and test the models.

12. Boston Airbnb Price Prediction

This project involves building a machine learning model to predict the prices of Boston Airbnb listings based on various features. The dataset used in this project is the Boston Airbnb Open Data, which contains detailed information about the Airbnb listings in Boston, such as the type of room, neighborhood, and host information.

  • Project title: Boston Airbnb Price Prediction
  • Dataset used: Boston Airbnb Open Data
  • Difficulty level: 3
  • Concepts involved: Data preprocessing, feature engineering, machine learning, regression, evaluation metrics
  • Source code: https://github.com/shyhn/boston-airbnb

13. LSTM Load Forecasting

This project aims to predict the electricity load demand in the future using LSTM neural networks. The dataset used is the Global Energy Forecasting Competition 2012 (GEFCom2012) load forecasting dataset. The goal is to provide an accurate forecast of the electricity load to assist in better energy management and planning.

  • Project title: LSTM Load Forecasting
  • Dataset used: GEFCom2012 load forecasting dataset
  • Difficulty level: 3
  • Concepts involved: LSTM, time series forecasting, neural networks
  • Source code: https://github.com/dafrie/lstm-load-forecasting

14. Rainfall analysis of Maharashtra

Rainfall analysis of Maharashtra - Season/Month wise forecasting. Different methods have been used. The main goal of this project is to increase the performance of forecasted results during rainy seasons.

15. Global Temperature Change Prediction

A Data Science project that uses an ARIMA model for Time Series Forecasting, to predict the temperature of any given city across a specific time period.

16. Predicting Wind Speed and Direction

Predict wind speed and direction for a location using historical weather data. The project involves time series forecasting techniques such as LSTM, GRU, and Time Series Regression.

  • Project title: Predicting Wind Speed and Direction
  • Dataset used: National Oceanic and Atmospheric Administration (NOAA) dataset, Weather Underground dataset
  • Difficulty level: 3/5
  • Concepts involved: LSTM, GRU, Time Series Regression

17. Predicting Hospital Admissions

Predict hospital admissions for a hospital or a region using historical hospital admission data. The project involves time series forecasting techniques such as LSTM, GRU, and Time Series Regression.

  • Project title: Predicting Hospital Admissions
  • Dataset used: Healthcare Cost and Utilization Project (HCUP) dataset, Medicare dataset
  • Difficulty level: 3/5
  • Concepts involved: LSTM, GRU, Time Series Regression

18. Forex trading strategy

This project involves creating a trading strategy based on time series data of previous forex prices. You can use datasets such as the OANDA API or the Yahoo Finance API to get forex data.

  • Project title: Forex Trading Strategy
  • Dataset used: OANDA API, Yahoo Finance API
  • Difficulty level: 4
  • Concepts involved: Time series forecasting, LSTM, deep learning, algorithmic trading

19. Real-time Stock Price Prediction

Develop a model that predicts the stock price of a company in real-time using historical stock data and relevant news articles.

  • Dataset used: Historical stock data and news articles
  • Difficulty level: 4
  • Concepts involved: Natural Language Processing (NLP), Time Series Analysis, Deep Learning

20. Predicting Solar Energy Output

Develop a model that predicts the output of solar energy systems based on historical energy production data and relevant environmental factors.

  • Dataset used: Historical solar energy production data and weather data
  • Difficulty level: 3
  • Concepts involved: Time Series Analysis, Deep Learning

21. Forecasting Airline Passenger Traffic using ARIMA Models

This project involves forecasting airline passenger traffic using ARIMA models. The dataset can be obtained from the Federal Aviation Administration (FAA) or the Bureau of Transportation Statistics (BTS), and the difficulty level is intermediate. Concepts involved include data preprocessing, time series analysis, and ARIMA models.

Project title: Forecasting Airline Passenger Traffic using ARIMA Models
Dataset used: Airline passenger traffic data from FAA or BTS
Difficulty level: 3/5
Concepts involved: Data preprocessing, time series analysis, ARIMA models

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21 Time Series/ Forecasting Project Ideas in DL/ML
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