Machine Learning with Scikit-learn
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Python for Applied Machine Learning – Getting Started & EDA
Import ML Libraries
Video - 00:19:38 mins
Exploratory Data Analysis (EDA) - Part 1
Video - 00:17:1 mins
Exploratory Data Analysis (EDA) - Part 2
Video - 00:12:53 mins
Split Data
Video - 00:10:57 mins
Develop ML Models and check accuracy score
Video - 00:10:47 mins
Classification Report
Video - 00:6:49 mins
Accuracy precision recall and f1
Video - 00:2:14 mins
Recap
Video - 00:15:46 mins
Confusion Matrix
Video - 00:6:47 mins
Glimpses of hyperparameter training estimators
Video - 00:5:14 mins
Save and load the model
Video - 00:4:8 mins
LinearSVC
Video - 00:8:14 mins
NeighborsClassifier
Video - 00:6:20 mins
Run multiple models using Functions
Video - 00:11:47 mins
Run multiple models using Parallel
Video - 00:10:9 mins
Cross Validation Score
Video - 00:13:19 mins
Predict vs Predict Proba
Video - 00:4:37 mins
ROC Curve
Video - 00:15:22 mins
Cross tab
Video - 00:1:59 mins
Correlation Analysis
Video - 00:5:30 mins
Feature Importance
Video - 00:10:35 mins
Hyperparameter tuning - Randomized SearchCV
Video - 00:15:7 mins
Hyperparameter tuning - GridSearchCV
Video - 00:8:19 mins
Classification Project - Heart Disease dataset
Video - 00:32:25 mins
Regressor - Train our model Part - 1
Video - 00:14:22 mins
Regressor - Train our model Part - 2
Video - 00:11:55 mins
Regressor - Recap
Video - 00:10:55 mins
Fill missing values using Pandas
Video - 00:20:41 mins
Fill missing values using scikit-learn libraries
Video - 00:21:47 mins
Regression Project - California Housing dataset
Video - 00:25:26 mins
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