Megha SinghalRandom Forest1.Random Forest is used for ensemble of decision trees. It uses base principle of bagging with random feature selection to create more…Apr 25, 2020Apr 25, 2020
Megha SinghalHow will you select the model ?1. The central issue in all of Machine Learning is “how do we extrapolate what has been learnt from a finite amount of data to all…Apr 24, 2020Apr 24, 2020
Megha SinghalLogistic RegressionA popular Binary Classification algorithm based on Supervised Learning.Apr 24, 2020Apr 24, 2020
Megha SinghalIntroduction to Machine LearningGathering Data — Quality and quantity of data that you gather will directly determine how good your predictive model can be. Some models…Apr 21, 2020Apr 21, 2020
Megha SinghalRegularization:This is a technique discourages learning a more flexible and complex model so as to avoid the risk of overfitting.Apr 20, 2020Apr 20, 2020
Megha SinghalinArtificial Intelligence in Plain EnglishNon-Probability DistributionIn previous blog we covered probability distribution and its types, now we proceed to Non-Probability distribution and its types.Apr 17, 2020Apr 17, 2020
Megha SinghalinAnalytics VidhyaMall Customers Cluster AnalysisProblem Statement: This data set is created only for the learning purpose of the customer segmentation concepts , also known as market…Apr 10, 20201Apr 10, 20201
Megha SinghalinAnalytics VidhyaXGBoost : “Thousand forests is in one acorn”Lets first understand what is XGBoost ?Apr 9, 2020Apr 9, 2020
Megha SinghalSampling TechniquesSampling is a process of drawing a predetermined number of observations from a larger population.It is difficult to collect the data from…Apr 9, 2020Apr 9, 2020