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[DesireCourse.Net] Udemy - Machine Learning Basics Classification models in Python
magnet:?xt=urn:btih:863d6437e156cbfad6dad218e677a6a171f2b964&dn=[DesireCourse.Net] Udemy - Machine Learning Basics Classification models in Python
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文件列表详情
863d6437e156cbfad6dad218e677a6a171f2b964
infohash:
52
文件数量
2.15 GB
文件大小
2021-10-8 07:08
创建日期
2024-6-22 09:05
最后访问
相关分词
DesireCourse
Net
Udemy
-
Machine
Learning
Basics
Classification
models
in
Python
1. Introduction/1. Welcome to the course!.mp4 17.6 MB
2. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4 123.83 MB
2. Introduction to Machine Learning/2. Building a Machine Learning model.mp4 45.27 MB
3. Basics of Statistics/1. Types of Data.mp4 25.86 MB
3. Basics of Statistics/2. Types of Statistics.mp4 13.24 MB
3. Basics of Statistics/3. Describing data Graphically.mp4 82.16 MB
3. Basics of Statistics/4. Measures of Centers.mp4 45.69 MB
3. Basics of Statistics/6. Measures of Dispersion.mp4 28.38 MB
4. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp4 18.64 MB
4. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4 73.06 MB
4. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.mp4 51.28 MB
4. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.mp4 15.97 MB
4. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4 80.59 MB
4. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp4 73.66 MB
4. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.mp4 54.1 MB
4. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.mp4 56.4 MB
4. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.mp4 48.86 MB
5. Data Preprocessing/1. Gathering Business Knowledge.mp4 25.13 MB
5. Data Preprocessing/10. Outlier treatment in Python.mp4 58.44 MB
5. Data Preprocessing/12. Missing Value Imputation.mp4 27.56 MB
5. Data Preprocessing/13. Missing Value Imputation in Python.mp4 27.65 MB
5. Data Preprocessing/15. Seasonality in Data.mp4 20.88 MB
5. Data Preprocessing/16. Variable Transformation.mp4 15.29 MB
5. Data Preprocessing/17. Variable transformation and Deletion in Python.mp4 35.58 MB
5. Data Preprocessing/19. Dummy variable creation Handling qualitative data.mp4 40.6 MB
5. Data Preprocessing/2. Data Exploration.mp4 23.4 MB
5. Data Preprocessing/20. Dummy variable creation in Python.mp4 33.87 MB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.mp4 87.62 MB
5. Data Preprocessing/4. Data Import in Python.mp4 25.49 MB
5. Data Preprocessing/6. Univariate analysis and EDD.mp4 27.31 MB
5. Data Preprocessing/7. EDD in Python.mp4 97.09 MB
5. Data Preprocessing/9. Outlier Treatment.mp4 27.77 MB
6. Classification Models/1. Three Classifiers and the problem statement.mp4 22.93 MB
6. Classification Models/10. Confusion Matrix.mp4 26.65 MB
6. Classification Models/11. Making Confusion Matrix in Python.mp4 64.71 MB
6. Classification Models/12. Evaluating performance of model.mp4 42.79 MB
6. Classification Models/13. Evaluating model performance in Python.mp4 11.77 MB
6. Classification Models/15. Linear Discriminant Analysis.mp4 48.68 MB
6. Classification Models/16. LDA in Python.mp4 14.38 MB
6. Classification Models/18. Test-Train Split.mp4 45.69 MB
6. Classification Models/19. Test-Train Split in Python.mp4 43.1 MB
6. Classification Models/2. Why can't we use Linear Regression.mp4 20.4 MB
6. Classification Models/21. K-Nearest Neighbors classifier.mp4 83.57 MB
6. Classification Models/22. K-Nearest Neighbors in Python Part 1.mp4 45.85 MB
6. Classification Models/23. K-Nearest Neighbors in Python Part 2.mp4 51.98 MB
6. Classification Models/25. Understanding the results of classification models.mp4 45.98 MB
6. Classification Models/26. Summary of the three models.mp4 25.25 MB
6. Classification Models/3. Logistic Regression.mp4 39.11 MB
6. Classification Models/4. Training a Simple Logistic Model in Python.mp4 61.19 MB
6. Classification Models/6. Result of Simple Logistic Regression.mp4 31.15 MB
6. Classification Models/7. Logistic with multiple predictors.mp4 9.99 MB
6. Classification Models/8. Training multiple predictor Logistic model in Python.mp4 34.02 MB
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