vaibhav-cric Goto Github PK

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Type: User

Bio: Enthusiast to learn new and adapt new technologies.

vaibhav-cric's Projects

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

$fractal_hackerrank_hiring_challenge_1 icon$ fractal_hackerrank_hiring_challenge_1

$fractal_hackerrank_hiring_challenge_2 icon$ fractal_hackerrank_hiring_challenge_2

$fractal_hackerrank_hiring_challenge_3 icon$ fractal_hackerrank_hiring_challenge_3

hackathon_startupfunds

done extensive eda to get insights and applied binning,linear regularization with heavy regularization,decision tree and finally a random forest

housing_dataset

used linear regression to predict the sales price of house...also done feature engineering...also found out the most important features

my_first-repository

hello world in github

numpy_advanced_project

pandas_project

python_getting_started_project

python_intermediate_project

visualization_matplotlib_project

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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