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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 project, we are going to work on Deep Learning using H2O to predict Census income.
In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.
Learn to classify the sentiment of sentences from the Rotten Tomatoes dataset. You will be asked to label phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive.