Скачать или смотреть OPPE 1 Revision Session 1 | Machine Learning Practices | Session - 12

OPPE 1 Revision Session 1 | Machine Learning Practices | Session - 12

This session is collaborated with GIR House, one of the 12 Houses of IITM BS Degree

Please fill this feedback form to rate my sessions:
https://forms.gle/pMaacwzLzkt366dq8

In this session, we've covered:-
Concepts from Week 1 to Week 5
OPPE 1 Mock 1
OPPE 1 Mock 2

Kaggle notebooks 🔼 (Make sure to upvote them):
Concepts Revision code: https://www.kaggle.com/param302/mlp-s...
OPPE 1 Mock 1 solutions: https://www.kaggle.com/code/param302/...
OPPE 1 Mock 2 solutions: https://www.kaggle.com/code/param302/...

Want to attend my Live Sessions?
I usually take them twice a week - Wednesday & Sunday, at 6 pm.

You can join my session calendar for details and meet links:
https://calendar.google.com/calendar/...

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



Follow me on my social handles:
Bio link 🔗 https://param302.bio.link
Twitter 🔗   / param3021  
LinkedIn 🔗   / param302  
Github 🔗 https://github.com/Param302
Kaggle 🔗 https://kaggle.com/param302