Udemy Machine Learning Project Heart Attack Prediction Analysis

Files Included :

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