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Udemy - Support Vector Machines in Python - SVM in Python 2019 [GC]

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Udemy - Support Vector Machines in Python - SVM in Python 2019 [GC] (Size: 2.3 GB)
  1. Bonus Lecture.html 1.6 KB
  1. Course flow.mp4 9.8 MB
  1. Course flow.srt 1.7 KB
  1. Gathering Business Knowledge.mp4 22.3 MB
  1. Gathering Business Knowledge.srt 3.9 KB
  1. Installing Python and Anaconda.mp4 18.6 MB
  1. Installing Python and Anaconda.srt 2.6 KB
  1. Introduction to Machine Learning.mp4 123.3 MB
  1. Introduction to Machine Learning.srt 18.4 KB
  1. Kernel Based Support Vector Machines.mp4 45.7 MB
  1. Kernel Based Support Vector Machines.srt 6.4 KB
  1. Regression and Classification Models.mp4 5.2 MB
  1. Regression and Classification Models.srt 819.2 B
  1. Support Vector classifiers.mp4 64.1 MB
  1. Support Vector classifiers.srt 9.7 KB
  1.1 Resources.zip 1.4 MB
  10. Missing Value Imputation in Python.mp4 23.4 MB
  10. Missing Value Imputation in Python.srt 4.1 KB
  10. The Data set for the Classification problem.mp4 22 MB
  10. The Data set for the Classification problem.srt 1.8 KB
  10. Working with Seaborn Library of Python.mp4 48.6 MB
  10. Working with Seaborn Library of Python.srt 7.5 KB
  11. Classification model - Preprocessing.mp4 54.5 MB
  11. Classification model - Preprocessing.srt 8.2 KB
  11. Seasonality in Data.mp4 17 MB
  11. Seasonality in Data.srt 3.8 KB
  12. Bi-variate analysis and Variable transformation.mp4 100.4 MB
  12. Bi-variate analysis and Variable transformation.srt 18.3 KB
  12. Classification model - Standardizing the data.mp4 11.9 MB
  12. Classification model - Standardizing the data.srt 1.8 KB
  13. SVM Based classification model.mp4 78.5 MB
  13. SVM Based classification model.srt 11.5 KB
  13. Variable transformation and deletion in Python.mp4 44.1 MB
  13. Variable transformation and deletion in Python.srt 7.5 KB
  14. Hyper Parameter Tuning.mp4 70.8 MB
  14. Hyper Parameter Tuning.srt 9.8 KB
  14. Non-usable variables.mp4 20.2 MB
  14. Non-usable variables.srt 5.4 KB
  15. Dummy variable creation Handling qualitative data.mp4 36.8 MB
  15. Dummy variable creation Handling qualitative data.srt 4.9 KB
  15. Polynomial Kernel with Hyperparameter Tuning.mp4 22.9 MB
  15. Polynomial Kernel with Hyperparameter Tuning.srt 4.1 KB
  16. Dummy variable creation in Python.mp4 26.5 MB
  16. Dummy variable creation in Python.srt 5.5 KB
  16. Radial Kernel with Hyperparameter Tuning.mp4 45.7 MB
  16. Radial Kernel with Hyperparameter Tuning.srt 6.6 KB
  17. Correlation Analysis.mp4 71.6 MB
  17. Correlation Analysis.srt 11 KB
  18. Correlation Analysis in Python.mp4 55.3 MB
  18. Correlation Analysis in Python.srt 6.6 KB
  2. Building a Machine Learning Model.mp4 44.9 MB
  2. Building a Machine Learning Model.srt 9.7 KB
  2. Course resources.html 102.4 B
  2. Data Exploration.mp4 20.5 MB
  2. Data Exploration.srt 3.6 KB
  2. Limitations of Support Vector Classifiers.mp4 13 MB
  2. Limitations of Support Vector Classifiers.srt 1.6 KB
  2. Quiz.html 204.8 B
  2. The Concept of a Hyperplane.mp4 35.3 MB
  2. The Concept of a Hyperplane.srt 4.8 KB
  2. The Data set for the Regression problem.mp4 41.7 MB
  2. The Data set for the Regression problem.srt 3 KB
  2.1 Files_svm_py.zip 1.8 MB
  3. Importing data for regression model.mp4 32.2 MB
  3. Importing data for regression model.srt 5.3 KB
  3. Maximum Margin Classifier.mp4 26.2 MB
  3. Maximum Margin Classifier.srt 83 MB
  3. Opening Jupyter Notebook.mp4 73 MB
  3. Opening Jupyter Notebook.srt 9.1 KB
  3. Quiz.html 204.8 B
  3. The Dataset and the Data Dictionary.mp4 69.4 MB
  3. The Dataset and the Data Dictionary.srt 7.8 KB
  4. Importing Data in Python.mp4 27.8 MB
  4. Importing Data in Python.srt 5.6 KB
  4. Introduction to Jupyter.mp4 50.9 MB
  4. Introduction to Jupyter.srt 12.4 KB
  4. Limitations of Maximum Margin Classifier.mp4 12.5 MB
  4. Limitations of Maximum Margin Classifier.srt 2.4 KB
  4. Missing value treatment.mp4 22.3 MB
  4. Missing value treatment.srt 3.1 KB
  4.1 House_Price.csv 53.5 KB
  5. Arithmetic operators in Python Python Basics.mp4 15.9 MB
  5. Arithmetic operators in Python Python Basics.srt 29.1 MB
  5. Dummy Variable creation.mp4 31.7 MB
  5. Dummy Variable creation.srt 4.7 KB
  5. Univariate analysis and EDD.mp4 24.2 MB
  5. Univariate analysis and EDD.srt 3.4 KB
  6. EDD in Python.mp4 61.8 MB
  6. EDD in Python.srt 10.4 KB
  6. Strings in Python Python Basics.mp4 80 MB
  6. Strings in Python Python Basics.srt 16.4 KB
  6. X-y Split.mp4 19.4 MB
  6. X-y Split.srt 3.8 KB
  7. Lists, Tuples and Directories Python Basics.mp4 73.2 MB
  7. Lists, Tuples and Directories Python Basics.srt 17 KB
  7. Outlier Treatment.mp4 24.5 MB
  7. Outlier Treatment.srt 4.5 KB
  7. Test-Train Split.mp4 27.5 MB
  7. Test-Train Split.srt 5.8 KB
  8. Outlier Treatment in Python.mp4 70.2 MB
  8. Outlier Treatment in Python.srt 13 KB
  8. Standardizing the data.mp4 47.3 MB
  8. Standardizing the data.srt 6.2 KB
  8. Working with Numpy Library of Python.mp4 53.8 MB
  8. Working with Numpy Library of Python.srt 10.5 KB
  9. Missing Value Imputation.mp4 25 MB
  9. Missing Value Imputation.srt 4.1 KB
  9. SVM based Regression Model in Python.mp4 79.8 MB
  9. SVM based Regression Model in Python.srt 9.7 KB
  9. Working with Pandas Library of Python.mp4 56.1 MB
  9. Working with Pandas Library of Python.srt 8.2 KB
  9.1 Customer.csv 64 KB
  Readme.txt 921.6 B
  [GigaCourse.com].url 0 B
  ▲ 115 total files

Description


Udemy - Support Vector Machines in Python - SVM in Python 2019

You're looking for a complete Support Vector Machines course that teaches you everything you need to create a Support Vector Machines model in Python, right? You've found the right Support Vector Machines techniques course! A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course.

For more Udemy Courses: https://gigacourse.com

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