Please note that this page does not hosts or makes available any of the listed filenames. You
cannot download any of those files from here.
|
1. Dropping Columns with Low Correlation.mp4 |
24.77MB |
1. Dropping Columns with Low Correlation.srt |
5.19KB |
1. Examining Missing Values.mp4 |
42.38MB |
1. Examining Missing Values.srt |
13.18KB |
1. First Step to the Hearth Attack Prediction Project.mp4 |
108.57MB |
1. First Step to the Hearth Attack Prediction Project.srt |
21.40KB |
1. Logistic Regression.mp4 |
27.30MB |
1. Logistic Regression.srt |
9.07KB |
1. Machine Learning with Real Hearth Attack Prediction Project.html |
266B |
1. Numeric Variables (Analysis with Distplot) Lesson 1.mp4 |
74.57MB |
1. Numeric Variables (Analysis with Distplot) Lesson 1.srt |
20.18KB |
1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4 |
45.33MB |
1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.srt |
11.32KB |
1. Project Conclusion and Sharing.mp4 |
26.95MB |
1. Project Conclusion and Sharing.srt |
4.91KB |
1. Required Python Libraries.mp4 |
58.76MB |
1. Required Python Libraries.srt |
12.84KB |
10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4 |
10.62MB |
10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.srt |
3.10KB |
10. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4 |
64.00MB |
10. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.srt |
15.39KB |
11. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 1.mp4 |
35.96MB |
11. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 1.srt |
10.15KB |
11. Separating Data into Test and Training Set.mp4 |
27.77MB |
11. Separating Data into Test and Training Set.srt |
9.45KB |
12. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 2.mp4 |
32.78MB |
12. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 2.srt |
10.35KB |
13. Relationships between variables (Analysis with Heatmap) Lesson 1.mp4 |
33.73MB |
13. Relationships between variables (Analysis with Heatmap) Lesson 1.srt |
8.68KB |
14. Relationships between variables (Analysis with Heatmap) Lesson 2.mp4 |
82.49MB |
14. Relationships between variables (Analysis with Heatmap) Lesson 2.srt |
16.04KB |
2. Cross Validation.mp4 |
28.16MB |
2. Cross Validation.srt |
7.63KB |
2. Examining Unique Values.mp4 |
41.01MB |
2. Examining Unique Values.srt |
12.93KB |
2. FAQ about Machine Learning, Data Science.html |
15.29KB |
2. Loading the Statistics Dataset in Data Science.mp4 |
9.32MB |
2. Loading the Statistics Dataset in Data Science.srt |
2.68KB |
2. Numeric Variables (Analysis with Distplot) Lesson 2.mp4 |
18.33MB |
2. Numeric Variables (Analysis with Distplot) Lesson 2.srt |
5.28KB |
2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4 |
32.76MB |
2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.srt |
9.66KB |
2. Visualizing Outliers.mp4 |
32.72MB |
2. Visualizing Outliers.srt |
11.86KB |
3. Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4 |
69.02MB |
3. Categoric Variables (Analysis with Pie Chart) Lesson 1.srt |
19.70KB |
3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4 |
22.32MB |
3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.srt |
4.99KB |
3. Dealing with Outliers – Trtbps Variable Lesson 1.mp4 |
39.97MB |
3. Dealing with Outliers – Trtbps Variable Lesson 1.srt |
13.66KB |
3. Initial analysis on the dataset.mp4 |
58.67MB |
3. Initial analysis on the dataset.srt |
18.18KB |
3. Notebook Design to be Used in the Project.mp4 |
97.66MB |
3. Notebook Design to be Used in the Project.srt |
20.32KB |
3. Roc Curve and Area Under Curve (AUC).mp4 |
38.63MB |
3. Roc Curve and Area Under Curve (AUC).srt |
10.20KB |
3. Separating variables (Numeric or Categorical).mp4 |
14.74MB |
3. Separating variables (Numeric or Categorical).srt |
4.63KB |
4. Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4 |
77.98MB |
4. Categoric Variables (Analysis with Pie Chart) Lesson 2.srt |
20.92KB |
4. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.mp4 |
52.33MB |
4. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.srt |
16.70KB |
4. Dealing with Outliers – Trtbps Variable Lesson 2.mp4 |
40.84MB |
4. Dealing with Outliers – Trtbps Variable Lesson 2.srt |
15.20KB |
4. Examining Statistics of Variables.mp4 |
84.27MB |
4. Examining Statistics of Variables.srt |
24.61KB |
4. Hyperparameter Optimization (with GridSearchCV).mp4 |
54.75MB |
4. Hyperparameter Optimization (with GridSearchCV).srt |
17.41KB |
4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html |
108B |
5. Dealing with Outliers – Thalach Variable.mp4 |
33.69MB |
5. Dealing with Outliers – Thalach Variable.srt |
11.17KB |
5. Decision Tree Algorithm.mp4 |
24.03MB |
5. Decision Tree Algorithm.srt |
7.39KB |
5. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.mp4 |
26.56MB |
5. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.srt |
7.09KB |
5. Examining the Missing Data According to the Analysis Result.mp4 |
49.98MB |
5. Examining the Missing Data According to the Analysis Result.srt |
13.88KB |
5. Examining the Project Topic.mp4 |
71.67MB |
5. Examining the Project Topic.srt |
13.93KB |
6. Dealing with Outliers – Oldpeak Variable.mp4 |
33.33MB |
6. Dealing with Outliers – Oldpeak Variable.srt |
10.95KB |
6. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.mp4 |
43.90MB |
6. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.srt |
8.91KB |
6. Recognizing Variables In Dataset.mp4 |
115.34MB |
6. Recognizing Variables In Dataset.srt |
23.83KB |
6. Support Vector Machine Algorithm.mp4 |
22.69MB |
6. Support Vector Machine Algorithm.srt |
6.62KB |
7. Determining Distributions of Numeric Variables.mp4 |
23.33MB |
7. Determining Distributions of Numeric Variables.srt |
6.54KB |
7. Feature Scaling with the Robust Scaler Method.mp4 |
32.65MB |
7. Feature Scaling with the Robust Scaler Method.srt |
11.66KB |
7. Random Forest Algorithm.mp4 |
27.73MB |
7. Random Forest Algorithm.srt |
8.38KB |
8. Creating a New DataFrame with the Melt() Function.mp4 |
48.78MB |
8. Creating a New DataFrame with the Melt() Function.srt |
15.14KB |
8. Hyperparameter Optimization (with GridSearchCV).mp4 |
48.56MB |
8. Hyperparameter Optimization (with GridSearchCV).srt |
14.42KB |
8. Transformation Operations on Unsymmetrical Data.mp4 |
22.18MB |
8. Transformation Operations on Unsymmetrical Data.srt |
6.32KB |
9. Applying One Hot Encoding Method to Categorical Variables.mp4 |
22.41MB |
9. Applying One Hot Encoding Method to Categorical Variables.srt |
7.63KB |
9. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 1.mp4 |
39.27MB |
9. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 1.srt |
8.33KB |
Bonus Resources.txt |
386B |
Get Bonus Downloads Here.url |
183B |