vaibhav-cric's repositories
Antallagma-Trade-Forecast
Used linear regression, XGBoost , Naive forecast, simple moving average, exponential moving average and time series model ARIMA to forecast the number of sales as well as the price
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housing_dataset
used linear regression to predict the sales price of house...also done feature engineering...also found out the most important features
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hackathon_startupfunds
done extensive eda to get insights and applied binning,linear regularization with heavy regularization,decision tree and finally a random forest
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xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
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my_first-repository
hello world in github
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