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

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[GigaCourse.com] Udemy - Support Vector Machines in Python - SVM in Python 2019 1. Setting up Python and Python Crash Course
  • 1. Installing Python and Anaconda.mp4 (18.6 MB)
  • 1. Installing Python and Anaconda.srt (2.6 KB)
  • 10. Working with Seaborn Library of Python.mp4 (48.6 MB)
  • 10. Working with Seaborn Library of Python.srt (7.5 KB)
  • 2. Course resources.html (0.1 KB)
  • 2.1 Files_svm_py.zip (1.8 MB)
  • 3. Opening Jupyter Notebook.mp4 (73.0 MB)
  • 3. Opening Jupyter Notebook.srt (9.1 KB)
  • 4. Introduction to Jupyter.mp4 (50.9 MB)
  • 4. Introduction to Jupyter.srt (12.4 KB)
  • 5. Arithmetic operators in Python Python Basics.mp4 (15.9 MB)
  • 5. Arithmetic operators in Python Python Basics.srt (29.1 MB)
  • 6. Strings in Python Python Basics.mp4 (80.0 MB)
  • 6. Strings in Python Python Basics.srt (16.4 KB)
  • 7. Lists, Tuples and Directories Python Basics.mp4 (73.2 MB)
  • 7. Lists, Tuples and Directories Python Basics.srt (17.0 KB)
  • 8. Working with Numpy Library of Python.mp4 (53.8 MB)
  • 8. Working with Numpy Library of Python.srt (10.5 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 (64.0 KB)
2. Machine Learning Basics
  • 1. Introduction to Machine Learning.mp4 (123.3 MB)
  • 1. Introduction to Machine Learning.srt (18.4 KB)
  • 2. Building a Machine Learning Model.mp4 (44.9 MB)
  • 2. Building a Machine Learning Model.srt (9.7 KB)
3. Maximum Margin Classifier
  • 1. Course flow.mp4 (9.8 MB)
  • 1. Course flow.srt (1.7 KB)
  • 1.1 Resources.zip (1.4 MB)
  • 2. The Concept of a Hyperplane.mp4 (35.3 MB)
  • 2. The Concept of a Hyperplane.srt (4.8 KB)
  • 3. Maximum Margin Classifier.mp4 (26.2 MB)
  • 3. Maximum Margin Classifier.srt (83.0 MB)
  • 4. Limitations of Maximum Margin Classifier.mp4 (12.5 MB)
  • 4. Limitations of Maximum Margin Classifier.srt (2.4 KB)
4. Support Vector Classifier
  • 1. Support Vector classifiers.mp4 (64.1 MB)
  • 1. Support Vector classifiers.srt (9.7 KB)
  • 2. Limitations of Support Vector Classifiers.mp4 (13.0 MB)
  • 2. Limitations of Support Vector Classifiers.srt (1.6 KB)
  • 3. Quiz.html (0.2 KB)
5. Support Vector Machines
  • 1. Kernel Based Support Vector Machines.mp4 (45.7 MB)
  • 1. Kernel Based Support Vector Machines.srt (6.4 KB)
  • 2. Quiz.html (0.2 KB)
  • 3. Quiz.html (0.2 KB)
6. Creating Support Vector Machine Model in Python
  • 1. Regression and Classification Models.mp4 (5.2 MB)
  • 1. Regression and Classification Models.srt (0.8 KB)
  • 10. The Data set for the Classification problem.mp4 (22.0 MB)
  • 10. The Data set for the Classification problem.srt (1.8 KB)
  • 11. Classification model - Preprocessing.mp4 (54.5 MB)
  • 11. Classification model - Preprocessing.srt (8.2 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)
  • 14. Hyper Parameter Tuning.mp4 (70.8 MB)
  • 14. Hyper Parameter Tuning.srt (9.8 KB)
  • 15. Polynomial Kernel with Hyperparameter Tuning.mp4 (22.9 MB)
  • 15. Polynomial Kernel with Hyperparameter Tuning.srt (4.1 KB)
  • 16. Radial Kernel with Hyperparameter Tuning.mp4 (45.7 MB)
  • 16. Radial Kernel with Hyperparameter Tuning.srt (6.6 KB)
  • 2. The Data set for the Regression problem.mp4 (41.7 MB)
  • 2. The Data set for the Regression problem.srt (3.0 KB)
  • 3. Importing data for regression model.mp4 (32.2 MB)
  • 3. Importing data for regression model.srt (5.3 KB)
  • 4. Missing value treatment.mp4 (22.3 MB)
  • 4. Missing value treatment.srt (3.1 KB)
  • 5. Dummy Variable creation.mp4 (31.7 MB)
  • 5. Dummy Variable creation.srt (4.7 KB)
  • 6. X-y Split.mp4 (19.4 MB)
  • 6. X-y Split.srt (3.8 KB)
  • 7. Test-Train Split.mp4 (27.5 MB)
  • 7. Test-Train Split.srt (5.8 KB)
  • 8. Standardizing the data.mp4 (47.3 MB)
  • 8. Standardizing the data.srt (6.2 KB)
  • 9. SVM based Regression Model in Python.mp4 (79.8 MB)
  • 9. SVM based Regression Model in Python.srt (9.7 KB)
7. Bonus Section
  • 1. Bonus Lecture.html (1.6 KB)
8. Appendix 1 Data Preprocessing
  • 1. Gathering Business Knowledge.mp4 (22.3 MB)
  • 1. Gathering Business Knowledge.srt (3.9 KB)
  • 10. Missing Value Imputation in Python.mp4 (23.4 MB)
  • 10. Missing Value Imputation in Python.srt (4.1 KB)
  • 11. Seasonality in Data.mp4 (17.0 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)
  • 13. Variable transformation and deletion in Python.mp4 (44.1 MB)
  • 13. Variable transformation and deletion in Python.srt (7.5 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)
  • 16. Dummy variable creation in Python.mp4 (26.5 MB)
  • 16. Dummy variable creation in Python.srt (5.5 KB)
  • 17. Correlation Analysis.mp4 (71.6 MB)
  • 17. Correlation Analysis.srt (11.0 KB)
  • 18. Correlation Analysis in Python.mp4 (55.3 MB)
  • 18. Correlation Analysis in Python.srt (6.6 KB)
  • 2. Data Exploration.mp4 (20.5 MB)
  • 2. Data Exploration.srt (3.6 KB)
  • 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)

  • Description

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



    Description

    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!

    How this course will help you?

    A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course.

    If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the advanced technique of machine learning, which are Support Vector Machines.

    Why should you choose this course?

    This course covers all the steps that one should take while solving a business problem through Decision tree.

    Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.

    What makes us qualified to teach you?

    The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course

    We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones:

    This is very good, i love the fact the all explanation given can be understood by a layman - Joshua

    Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy

    Our Promise

    Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.

    Download Practice files, take Quizzes, and complete Assignments

    With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning.

    Go ahead and click the enroll button, and I'll see you in lesson 1!

    Cheers

    Start-Tech Academy


    Created by Start-Tech Academy
    Last updated 3/2020
    English
    English [Auto-generated]



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

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2.3 GB
seeders:6
leechers:8
Udemy - Support Vector Machines in Python - SVM in Python 2019

Torrent hash: A776E8269FEE689E79C72BA5C8492B0A47240553