A Machine Learning project for Machine Learning Internship offered by InternshipStudio.

Youtube advertisers pay content creators based on adviews and clicks for the goods and services being marketed. They want to estimate the adview based on other metrics like comments, likes etc. The problem statement is therefore to train various regression models and choose the best one to predict the number of adviews.

To build a machine learning model which will predict youtube adview count based on other youtube metrics.

• train.csv - the training set
• test.csv - the test set
• The file train.csv contains metrics and other details of about 15000 youtube videos. The metrics include number of views, likes, dislikes, comments and apart from that published date, duration and category are also included. The train.csv file also contains the metric number of adviews which is our target variable for prediction.

• Machine Learning
• GradientBoostingRegressor
• XGBRegressor
• LGBMRegressor
• StackingRegressor
• Lasso
• Ridge
• Optuna

Made With ❤️ by Utkarsh Kharche

Any issues??? Feel free to ask.Linkedin

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