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TORRENT DETAILS
Udemy - Machine Learning Mastery - From Data To Advanced Classifiers
TORRENT SUMMARY
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Mastering Machine Learning: From Data Import to Model Evaluation with Advanced Classifiers
What you'll learn:
Importing and preparing data for analysis.
Cleaning and preprocessing techniques for data integrity.
Effective data visualization methods.
Understanding and utilizing correlation heatmaps.
Preprocessing steps for feature scaling and handling categorical variables.
Proper data splitting for training and testing.
Implementation of machine learning models: Support Vector Classifier (SVC), RandomForestClassifier, XGBClassifier, KNeighborsClassifier, LGBMClassifier
Evaluation using Receiver Operator Characteristic (ROC) curve.
Requirements:
Basic understanding of programming concepts and Python programming language.
Familiarity with data manipulation using libraries such as Pandas and NumPy.
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FILE LIST
Filename
Size
~Get Your Files Here !/1. Introduction/1. Introduction.mp4
28.1 MB
~Get Your Files Here !/1. Introduction/2. Installing Jupyter.mp4
36.8 MB
~Get Your Files Here !/1. Introduction/3. How to download Python files.mp4
33.3 MB
~Get Your Files Here !/2. Course Contents/1. Import Data.mp4
105 MB
~Get Your Files Here !/2. Course Contents/1.1 File 1.ipynb
11.6 KB
~Get Your Files Here !/2. Course Contents/10. 10 displaying the distribution of the data using a box plot.mp4
95.5 MB
~Get Your Files Here !/2. Course Contents/10.1 File 10.ipynb
432 KB
~Get Your Files Here !/2. Course Contents/11. 11 displaying the distribution of the data by the different categories.mp4
133.9 MB
~Get Your Files Here !/2. Course Contents/11.1 File 11.ipynb
535.1 KB
~Get Your Files Here !/2. Course Contents/12. 12 visualize the relationship between two variables with jointplot.mp4
135.2 MB
~Get Your Files Here !/2. Course Contents/12.1 File 12.ipynb
955.8 KB
~Get Your Files Here !/2. Course Contents/13. 13 calculating the correlation matrix of the DataFrame.mp4
84.9 MB
~Get Your Files Here !/2. Course Contents/13.1 File 13.ipynb
969.4 KB
~Get Your Files Here !/2. Course Contents/14. 14 creating a mask using NumPy.mp4
57.2 MB
~Get Your Files Here !/2. Course Contents/14.1 File 14.ipynb
972.2 KB
~Get Your Files Here !/2. Course Contents/15. 15 creating a color map using seaborn.mp4
33.6 MB
~Get Your Files Here !/2. Course Contents/15.1 File 15.ipynb
978.1 KB
~Get Your Files Here !/2. Course Contents/16. 16 creating a heatmap using seaborn.mp4
88.8 MB
~Get Your Files Here !/2. Course Contents/16.1 File 16.ipynb
1 MB
~Get Your Files Here !/2. Course Contents/17. 17 calculating the number of outliers.mp4
218.3 MB
~Get Your Files Here !/2. Course Contents/17.1 File 17.ipynb
1.1 MB
~Get Your Files Here !/2. Course Contents/18. 18 standardizing features.mp4
58.8 MB
~Get Your Files Here !/2. Course Contents/18.1 File 18.ipynb
71.8 KB
~Get Your Files Here !/2. Course Contents/19. 19 Hypothesis testing.mp4
34.9 MB
~Get Your Files Here !/2. Course Contents/19.1 File 19.ipynb
75.5 KB
~Get Your Files Here !/2. Course Contents/2. 2 visualizing missing data in a dataset.mp4
34.3 MB
~Get Your Files Here !/2. Course Contents/2.1 File 2.ipynb
90.8 KB
~Get Your Files Here !/2. Course Contents/20. 20 Normalization.mp4
131.9 MB
~Get Your Files Here !/2. Course Contents/20.1 File 20.ipynb
112.4 KB
~Get Your Files Here !/2. Course Contents/21. 21 split the data into training and testing sets.mp4
147 MB
~Get Your Files Here !/2. Course Contents/21.1 File 21.ipynb
141.8 KB
~Get Your Files Here !/2. Course Contents/22. 22 Start traning SVC and Learn Hyperparameters.mp4
62.6 MB
~Get Your Files Here !/2. Course Contents/22.1 File 22.ipynb
144.5 KB
~Get Your Files Here !/2. Course Contents/23. 23 find the best hyperparameter.mp4
100.4 MB
~Get Your Files Here !/2. Course Contents/23.1 File 23.ipynb
147.6 KB
~Get Your Files Here !/2. Course Contents/24. 24 make predictions on the test data and avaluate the model.mp4
134.8 MB
~Get Your Files Here !/2. Course Contents/24.1 File 24.ipynb
155.4 KB
~Get Your Files Here !/2. Course Contents/25. 25 Train RandomForestClassifier.mp4
101.8 MB
~Get Your Files Here !/2. Course Contents/25.1 File 25.ipynb
160.2 KB
~Get Your Files Here !/2. Course Contents/26. 26 Train XGBClassifier.mp4
63.7 MB
~Get Your Files Here !/2. Course Contents/26.1 File 26.ipynb
165.7 KB
~Get Your Files Here !/2. Course Contents/27. 27 Train KNeighborsClassifier.mp4
47.9 MB
~Get Your Files Here !/2. Course Contents/27.1 File 27.ipynb
171.2 KB
~Get Your Files Here !/2. Course Contents/28. 28 Train LGBMClassifier.mp4
59.8 MB
~Get Your Files Here !/2. Course Contents/28.1 File 28.ipynb
180.8 KB
~Get Your Files Here !/2. Course Contents/29. 29 calculate the (ROC) curve and the (AUC) score.mp4
104.9 MB
~Get Your Files Here !/2. Course Contents/29.1 File 29.ipynb
238 KB
~Get Your Files Here !/2. Course Contents/3. 3 calculating statistical information.mp4
57.9 MB
~Get Your Files Here !/2. Course Contents/3.1 File 3.ipynb
101.6 KB
~Get Your Files Here !/2. Course Contents/4. 4 checking for duplicate rows in the DataFrame.mp4
30.4 MB
~Get Your Files Here !/2. Course Contents/4.1 File 4.ipynb
103.1 KB
~Get Your Files Here !/2. Course Contents/5. 5 calculating the number of distinct values in each column.mp4
56.2 MB
~Get Your Files Here !/2. Course Contents/5.1 File 5.ipynb
105.6 KB
~Get Your Files Here !/2. Course Contents/6. 6 checking for missing or null values in the DataFrame.mp4
34.2 MB
~Get Your Files Here !/2. Course Contents/6.1 File 6.ipynb
117.3 KB
~Get Your Files Here !/2. Course Contents/7. 7 Cleaning the data.mp4
71.2 MB
~Get Your Files Here !/2. Course Contents/7.1 File 7.ipynb
128 KB
~Get Your Files Here !/2. Course Contents/8. 8 creating a new column called 'Label' in the DataFrame.mp4
78.7 MB
~Get Your Files Here !/2. Course Contents/8.1 File 8.ipynb
158.3 KB
~Get Your Files Here !/2. Course Contents/9. 9 creating a histogram plot.mp4
