Row 91523

Row ID: 91523 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 91523 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Basic Stats -- Expectation , Variance concepts, t test , p values , ANOVA , Hypothesis testing, Type 1 error , type 2 error. 2 sample ANOVA. L1 Norm, L2 Norm , Ridge ,Lasso , Cross Validation k fold and validation set., PCA , PCR. Bias variance tradeoff concepts. SVD Matrix decomps , Bootstrap, Bayesian Analysis , Random Forrest, Decision Tree ,CART , Bagging, Boosting, Stacking , PVC , Important components

Advanced Stats - Fairness studies , Conformal Predictions, Pattern Recognition, Double descent , Monte Carlo , Markov Chain Monte Carlo , Gibbs Sampling, K means Clustering, Gap statistics , KNN, Propensity Scores for Causal Models , Survival Analysis, Hazard Functions, Uplift Modeling.

Coming from a DS Masters Student about to join F100 company . Interview Experience with about 10 other companies and having asked multiple team leads about the concepts that they use. And also aggregating Interview Questions

FieldValue
text Basic Stats -- Expectation , Variance concepts, t test , p values , ANOVA , Hypothesis testing, Type 1 error , type 2 error. 2 sample ANOVA. L1 Norm, L2 Norm , Ridge ,Lasso , Cross Validation k fold and validation set., PCA , PCR. Bias variance tradeoff concepts. SVD Matrix decomps , Bootstrap, Bayesian Analysis , Random Forrest, Decision Tree ,CART , Bagging, Boosting, Stacking , PVC , Important components Advanced Stats - Fairness studies , Conformal Predictions, Pattern Recognition, D…
label r/datascience
dataType comment
communityName r/datascience
datetime 2024-05-25
username_encoded Z0FBQUFBQm5Lak1zQk56bWY5cWdsRjRQRzcwYlZWdC03ZHhTMXpFWF9vR0g2YnppeGxmeFZ3TFZ1bUtXUzdKdHNpYVU0aTJHYTRKZ0RRa253QTZjTkRucldjSmM3dzlNb0E9PQ==
url_encoded Z0FBQUFBQm5Lak85VVJ2V0t0a0EtZEJRU0g0V210b1IzVFZYUXNmWS01M3dfaFkxNWQ1WGtLdGszNllNYmpXZUloaHZHQjIwOVpYZ2JhMlhtSGRWR19KeDRuSnZlSVZXTm5CcFZrRC1VbXZiNWw1OUk4S0c2YjBMVlR2UWRBSEkyaUU3alJjRGJPeXNPa1BFUVg1WEd4N3FEUzdVd3Y4bHA2ZUswRXBrZkZkMnAzb1oyeUVFVDUyMExYc25OdW83ZG9iM3pZWU1Pc1R2ZktkOVRBcUY5dXJyRzNrMkF0NTgtdGc3QXdHMU84d0E0Y3MwNHRzbXF1dz0=

Raw Record

{
  "text": "Basic Stats -- Expectation , Variance concepts,  t test , p values , ANOVA , Hypothesis testing, Type 1 error , type 2 error. 2 sample ANOVA. L1 Norm, L2 Norm , Ridge ,Lasso ,  Cross Validation k fold and validation set., PCA , PCR. Bias variance tradeoff concepts. SVD Matrix decomps , Bootstrap, Bayesian Analysis , Random Forrest,  Decision Tree ,CART , Bagging, Boosting, Stacking , PVC ,  Important components \n\n\nAdvanced Stats - Fairness studies , Conformal Predictions,  Pattern Recognition, Double descent , Monte Carlo , Markov Chain Monte Carlo , Gibbs Sampling, K means Clustering, Gap statistics , KNN, Propensity Scores for Causal Models , Survival Analysis, Hazard Functions, Uplift Modeling.\n\n\nComing from a DS Masters Student  about to join F100 company . Interview Experience with about 10 other companies and having asked multiple team leads about the concepts that they use.  And also aggregating Interview Questions",
  "label": "r/datascience",
  "dataType": "comment",
  "communityName": "r/datascience",
  "datetime": "2024-05-25",
  "username_encoded": "Z0FBQUFBQm5Lak1zQk56bWY5cWdsRjRQRzcwYlZWdC03ZHhTMXpFWF9vR0g2YnppeGxmeFZ3TFZ1bUtXUzdKdHNpYVU0aTJHYTRKZ0RRa253QTZjTkRucldjSmM3dzlNb0E9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak85VVJ2V0t0a0EtZEJRU0g0V210b1IzVFZYUXNmWS01M3dfaFkxNWQ1WGtLdGszNllNYmpXZUloaHZHQjIwOVpYZ2JhMlhtSGRWR19KeDRuSnZlSVZXTm5CcFZrRC1VbXZiNWw1OUk4S0c2YjBMVlR2UWRBSEkyaUU3alJjRGJPeXNPa1BFUVg1WEd4N3FEUzdVd3Y4bHA2ZUswRXBrZkZkMnAzb1oyeUVFVDUyMExYc25OdW83ZG9iM3pZWU1Pc1R2ZktkOVRBcUY5dXJyRzNrMkF0NTgtdGc3QXdHMU84d0E0Y3MwNHRzbXF1dz0="
}
Explore Dataset Explore Row

Entry Information