2 тысяч подписчиков
121 видео
Categorical Features Encoding in Machine Learning| Feature Encoding Tutorial 1
Sklearn Robust Scaler in Machine Learning | Feature Scaling Tutorial 3
LabelEncoding and Ordinal Encoding of Ordinal Categorical Features| Feature Encoding Tutorial 2
Exhaustive Feature Selection | Wrapper Method Part 3 | Tutorial 9
Feature Selection Embedded Method Tree Based Algorithm Random Forest |Tutorial 11
When to use One-Hot , Label and Ordinal Encoding in Machine Learning | Feature Encoding Tutorial 4
Forward Feature Selection |Sequential Forward Selection|Wrapper Method Part1|Tutorial 7
Verifying the Assumptions of Linear Regression using Python and Stats Library|Part 2|Machines Learn
Feature Extraction in Machine Learning
Min-Max Scaler and Standard Scaler in Machine Learning | Feature Scaling Tutorial 2
Difference between Sklearn OneHotEncoder vs pd.get_dummies | Feature Encoding Tutorial 5
bias variance tradeoff in machine learning|Data Science
Precision Recall Curve in Machine Learning
Logistic Regression Mathematical Intuition Tutorial 1
Backward Feature Selection |Sequential Backward Selection|Wrapper Method Part 2|Tutorial 8
Handling Missing Data using Python dropna,replace,fillna,interpolation | Data Cleaning Tutorial 11
One-Hot and Dummy Encoding of Nominal Data in Machine Learning |Feature Encoding Tutorial 3
Dummy Variable Trap in Machine Learning | Feature Encoding Tutorial 6
Feature Selection Embedded Method Lasso L1 Regularization|Tutorial 10
Handling Missing Value with Mean Median and Mode Explanation | Data Cleaning Tutorial 7
Feature Engineering in Machine Learning and Data Science
Imbalanced Dataset and issue with imbalanced dataset | what is Under sampling and Oversampling Part1
What is Range is Statistics|Data Science|Machine Learning
Hands-on Handling missing value using Mean Median mode with Python | Data Cleaning Tutorial 8
Logistic Regression Geometrical Intuition Tutorial 2
Feature Selection using Remove Duplicate Numerical and Categorical Features - Tutorial 3
Feature Selection using ANOVA Test for Classification and Regression - Tutorial 4
Percentile and Quartile in Quartile Range |Statistics||Data Science|Machine Learning
List or Pairwise deletion of Missing Value | Data Cleaning Tutorial 5
Accuracy, Precision, Recall, TPR, FPR, Specificity, Sensitivity, F1 Score in Machine Learning
Univariate, Bivariate and Multivariate Analysis- EDA-Data Science
Frequency Encoding in Machine Learning | Feature Encoding Tutorial 7
Handling Duplicate Data using Python | Data Cleaning Tutorial 1
Missing Values Handling in Machine Learning | Data Cleaning Tutorial 4
Missing value handling using Prediction Model in Machine Learning | Data Cleaning Tutorial 9
Maximum log likelihood Intuition of Logistic Regression Tutorial 3
Categorical Feature selection using chi squared | Hands-on with Scipy and Python part1|Tutorial 12
Feature Selection using Correlation and Ranking Filter methods -Check Multi-collinearity- Tutorial 5
Categorical Feature selection using chi squared |Hands-on with Sklearn and Python part2|Tutorial 13
Credit Card defaulter Prediction using Logistic Regression Tutorial 5
underfitting and overfitting in machine learning and how to overcome underfitting and overfitting
Lasso(L1) ,Ridge(L2) and Elastic-Net(L1/L2) Regularization hands-on python in Machine Learning
Bias Variance in Machine Learning|Data Science
Confusion matrix, True Positive (TP), True Negative (TN), False Positive (FP),False Negative(FN)
