OPPE 1 Revision 2 with Practice Questions | Machine Learning Practices | Session - 13

OPPE 1 Revision 2 with Practice Questions | Machine Learning Practices | Session - 13
This session is collaborated with GIR House, one of the 12 Houses of IITM BS Degree
Access 50+ Practice Questions, NPPE & Mock Solutions in the feedback form:
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In this session, we've covered:-
- 20+ New Practice Questions
- Concepts Revision from Week 1 to Week 5
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I usually take them twice a week - Wednesday & Sunday, at 6 pm.
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Topics included in OPPE 1:
- Numpy
- Pandas
- Sklearn datasets
- Sklearn preprocessing
- Sklearn model selection
- Sklearn metrics
- Sklearn pipeline
- Sklearn feature selection
- Sklearn linear model
- Linear regression / SGD regressor
- Data Preprocessing
- Data Cleaning (Missing Values, Outliers)
- - SimpleImputer
- - KNNImputer
- Feature Engineering
- - Polynomial Features
- - Interaction Features
- Feature Transformation
- - Encoding
- - - OneHotEncoder
- - - OrdinalEncoder
- - - LabelEncoder
- Feature Selection
- - SelectKBest
- - SelectPercentile
- - RFE
- - RFECV
- - SelectFromModel
- - Mutual Information
- - VarianceThreshold
- - chi2
- Feature Scaling
- - StandardScaler
- - MinMaxScaler
- - MaxAbsScaler
- Model Pipeline
- - Pipeline
- - FeatureUnion
- - ColumnTransformer
- Linear Regression
- - Simple Linear Regression
- - SGD Regressor
- - Ridge Regression (L2)
- - Lasso Regression (L1)
- Cross Validation
- - ShuffleSplit
- - LeaveOneOut
- - KFold
- - StratifiedKFold
- Hyperparameter Tuning
- - GridSearchCV
- - RandomizedSearchCV
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