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DataScience
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	`1`	`+Statistics`
	`2`	`+ T test`
	`3`	`+ Z test`
	`4`	`+ ANOVA`
	`5`	`+ Chi Square`
	`6`	`+ Correlation`
	`7`	`+ Covariance`
	`8`	`+ Hypothesis Testing`
	`9`	`+`
	`10`	`+Classic ML`
	`11`	`+ Linear Regression`
	`12`	`+ Logistic Regression`
	`13`	`+ Regulazisation (Rigde and Lasso)`
	`14`	`+ Cost Functions`
	`15`	`+ Decision Tree`
	`16`	`+ Random Forest`
	`17`	`+ Ensemble Learning`
	`18`	`+ Bagging and Boosting`
	`19`	`+ XGBoost`
	`20`	`+ LightGBM`
	`21`	`+`
	`22`	`+Hyperparamter Tuning`
	`23`	`+ Grid Search`
	`24`	`+ Random Search`
	`25`	`+ HyperOpt`
	`26`	`+ Feature Selection - PCA`
	`27`	`+`
	`28`	`+Normmaliztion`
	`29`	`+ Imbalance Dataaet`
	`30`	`+ Imputing Missing data`
	`31`	`+ Handling Outliers`
	`32`	`+ Cross Validation`
	`33`	`+`
	`34`	`+Clustering`
	`35`	`+ K-Means clsutering`
	`36`	`+ KNN`
	`37`	`+ Principal Component Analysis`
	`38`	`+`
	`39`	`+Perfromance Measures`
	`40`	`+ R-square`
	`41`	`+ Adjusted R-square`
	`42`	`+ Mean Square Error`
	`43`	`+ Root Mean Square Error`
	`44`	`+ MAPE`
	`45`	`+ Mean Absolute Error`
	`46`	`+`
	`47`	`+ Recall`
	`48`	`+ Precision`
	`49`	`+ Accuracy`
	`50`	`+ F1-Score`
	`51`	`+ ROC-AUC`
	`52`	`+ Confusion Matrix`
	`53`	`+`
	`54`	`+ Type1 Error`
	`55`	`+ Type2 Error`
	`56`	`+ True Positive Rate`
	`57`	`+ False Positive Rate`
	`58`	`+`
	`59`	`+`
	`60`	`+Adavnced ML`
	`61`	`+ CNN`
	`62`	`+ RCNN`
	`63`	`+ LSTM`
	`64`	`+ Transfromers`
	`65`	`+ BERT`
	`66`	`+`
	`67`	`+`
	`68`	`+Time Series`
	`69`	`+ Trend`
	`70`	`+ Seasonality`
	`71`	`+ Irregualrity`
	`72`	`+ Cyclicity`
	`73`	`+ Stationality`
	`74`	`+ ADF`
	`75`	`+ Making data stationary`
	`76`	`+ White Noise`
	`77`	`+ Holt Winters`
	`78`	`+ FB-Prophet`
	`79`	`+`
	`80`	`+`
	`81`	`+Drift Detection`
	`82`	`+ Type of drifts`
	`83`	`+ KS Test`
	`84`	`+ KL Divergence`
	`85`	`+ Wassertein distance`
	`86`	`+ ADWIN`
	`87`	`+`
	`88`	`+NLP`
	`89`	`+ Stemming`
	`90`	`+ Lemmatization`
	`91`	`+ TF-IDF`
	`92`	`+ Word2Vec`
	`93`	`+ Bag of Words models`
	`94`	`+ Spacy`
	`95`	`+`
	`96`	`+MLOPS`
	`97`	`+ MLFlow`
	`98`	`+ Model Registry`
	`99`	`+ Data Versioning`
	`100`	`+ Artifacts`
	`101`	`+`
	`102`	`+`
	`103`	`+`

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