PinnedMahitha SingirikondainNerd For TechOverfitting : Identify and Resolve“It is better to be approximately right rather than precisely wrong.”- Warren BuffetJan 11, 2021Jan 11, 2021
Mahitha SingirikondainDataDrivenInvestorA thumbnail of Feature EngineeringYou can’t build a great building on a weak foundation. You must have a solid foundation if you’re going to have a strong super structure.Sep 6, 2021Sep 6, 2021
Mahitha SingirikondainDataDrivenInvestorHow to pick the best ML model ?Machine learning models are built on training data and then predictions are done to address the business problems. There are many models…Dec 28, 2020Dec 28, 2020
Mahitha SingirikondaHow Padding helps in CNN ?An approach to build an efficient model.Dec 22, 2020Dec 22, 2020
Mahitha SingirikondaWhy Pooling in CNN?Imagine you are scanning a 16X20 picture and a 2X2 same picture, which one do you think is scanned faster? Yes 2X2 would be faster with…Dec 13, 2020Dec 13, 2020
Mahitha SingirikondainDataDrivenInvestorScikit.101Your data speaks a lot, get to know what it is by using this Machine Learning Library.Dec 10, 2020Dec 10, 2020
Mahitha SingirikondaExample for XGBoostXG Boost is very powerful Machine learning algorithm which can have higher rates of accuracy when specified by its wide range of…Nov 6, 2020Nov 6, 2020
Mahitha SingirikondaWay to handle missing values-Proximity ImputationMissing data is a pool of problems in the world of data. Data professionals need complete data to analyze and hence are forced to drop the…Nov 2, 2020Nov 2, 2020
Mahitha SingirikondaXGBoost Hyperparameters OverviewIs your machine learning model taking time and you ever wonder if accuracy is moderate? XGBoost is the solution for you. Let us look at…Oct 13, 2020Oct 13, 2020
Mahitha SingirikondaBoostingBoosting is an ensemble meta-algorithm in machine learning to primarily minimize bias, as well as variance in supervised learning, and a…Oct 12, 2020Oct 12, 2020
