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We will try to predict how often players playing a video game called PLAYERUNKNOWNS BATTLEGROUNDS(more famously known as PUBG) will win when they play by themselves.
The data set provides information about players’ statistics for approximately 85,000 of the top PUBG players. All statistics were gathered using aggregate region filters (all regions) and feature labels are subdivided by server type: solo, duo, and squad. The data consists of 87,898 players with 150 numerical game-play features per player (+2 for the player name and PUBG Tracker ID).
In this data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
In this machine learning project, you will build predictive models to identify wine preferences of people using physiochemical properties of wines and help restaurants recommend the right quality of wine to a customer.