Course description

Video game sales prediction using machine learning is the process of using algorithms and statistical models to forecast the sales of video games. The goal is to analyze the historical data of video game sales, including factors such as platform, genre, publisher, and release date, and then use this data to predict future sales for upcoming games. Machine learning algorithms can help identify patterns and trends in the data, which can then be used to make accurate predictions about the sales potential of a new game. This information can be used by game developers and publishers to make informed decisions about marketing, pricing, and distribution strategies.

What will i learn?

• One of the primary outcomes of using machine learning for video game sales prediction is the ability to make accurate sales forecasts. By analyzing historical data and identifying patterns and trends, machine learning models can predict sales for upcoming games with a high degree of accuracy.
• Machine learning models can also help identify which marketing strategies are most effective for different types of video games. By analyzing historical data, machine learning algorithms can identify which marketing channels, messages, and tactics are most likely to drive sales for different types of games.
• Video game sales prediction using machine learning can also lead to enhanced revenue for game developers and publishers. By accurately predicting sales for upcoming games, developers can better plan production schedules and allocate resources to maximize revenue.
• Using machine learning for video game sales prediction can also help reduce the risk associated with developing and publishing new games. By accurately predicting sales, game developers and publishers can make more informed decisions about which games to invest in and which ones to pass on.