1. First Step to the Hearth Attack Prediction Project.mp4 (108.57 MB)
3. Notebook Design to be Used in the Project.mp4 (97.66 MB)
5. Examining the Project Topic.mp4 (71.67 MB)
6. Recognizing Variables In Dataset.mp4 (115.34 MB)
1. Required Python Libraries.mp4 (58.76 MB)
2. Loading the Statistics Dataset in Data Science.mp4 (9.32 MB)
3. Initial analysis on the dataset.mp4 (58.67 MB)
1. Examining Missing Values.mp4 (42.38 MB)
2. Examining Unique Values.mp4 (41.01 MB)
3. Separating variables (Numeric or Categorical).mp4 (14.74 MB)
4. Examining Statistics of Variables.mp4 (84.27 MB)
1. Numeric Variables (Analysis with Distplot) Lesson 1.mp4 (74.57 MB)
2. Numeric Variables (Analysis with Distplot) Lesson 2.mp4 (18.33 MB)
3. Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4 (69.02 MB)
4. Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4 (77.98 MB)
5. Examining the Missing Data According to the Analysis Result.mp4 (49.98 MB)
1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4 (45.33 MB)
10. Numerical Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4 (64 MB)
11. Numerical Categorical Variables (Analysis with Box Plot) Lesson 1.mp4 (35.96 MB)
12. Numerical Categorical Variables (Analysis with Box Plot) Lesson 2.mp4 (32.78 MB)
13. Relationships between variables (Analysis with Heatmap) Lesson 1.mp4 (33.73 MB)
14. Relationships between variables (Analysis with Heatmap) Lesson 2.mp4 (82.49 MB)
2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4 (32.76 MB)
3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4 (22.32 MB)
4. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.mp4 (52.33 MB)
5. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.mp4 (26.56 MB)
6. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.mp4 (43.9 MB)
7. Feature Scaling with the Robust Scaler Method.mp4 (32.65 MB)
8. Creating a New DataFrame with the Melt() Function.mp4 (48.78 MB)
9. Numerical Categorical Variables (Analysis with Swarm Plot) Lesson 1.mp4 (39.27 MB)
1. Dropping Columns with Low Correlation.mp4 (24.77 MB)
10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4 (10.62 MB)
11. Separating Data into Test and Training Set.mp4 (27.77 MB)
2. Visualizing Outliers.mp4 (32.72 MB)
3. Dealing with Outliers – Trtbps Variable Lesson 1.mp4 (39.97 MB)
4. Dealing with Outliers – Trtbps Variable Lesson 2.mp4 (40.84 MB)
5. Dealing with Outliers – Thalach Variable.mp4 (33.69 MB)
6. Dealing with Outliers – Oldpeak Variable.mp4 (33.33 MB)
7. Determining Distributions of Numeric Variables.mp4 (23.33 MB)
8. Transformation Operations on Unsymmetrical Data.mp4 (22.18 MB)
9. Applying One Hot Encoding Method to Categorical Variables.mp4 (22.41 MB)
1. Logistic Regression.mp4 (27.3 MB)
2. Cross Validation.mp4 (28.16 MB)
3. Roc Curve and Area Under Curve (AUC).mp4 (38.63 MB)
4. Hyperparameter Optimization (with GridSearchCV).mp4 (54.75 MB)
5. Decision Tree Algorithm.mp4 (24.03 MB)
6. Support Vector Machine Algorithm.mp4 (22.69 MB)
7. Random Forest Algorithm.mp4 (27.73 MB)
8. Hyperparameter Optimization (with GridSearchCV).mp4 (48.56 MB)
1. Project Conclusion and Sharing.mp4 (26.95 MB)