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10. ML Libraries in Python.mp4
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~Get Your Files Here !
1 - Introduction to Machine Learning
10 - Feature Engineering
11 - Saving & Loading Models
12 - Practical ML Projects
13 - Deployment Basics
14 - Best Practices & ML Workflow
15 - Interview Preparation
2 - Python for Machine Learning
3 - ML Libraries in Python
10. ML Libraries in Python.mp4
MP4
10.6 MB
11. NumPy Basics.mp4
MP4
4.7 MB
12. Pandas Basics.mp4
MP4
3.8 MB
13. Scikit-Learn basics.mp4
MP4
3.5 MB
14. Matplotlib & Seaborn basics.mp4
MP4
3.4 MB
15. SciPy basics.mp4
MP4
2.7 MB
4 - Data Handling & Preprocessing
16. Loading & Inspecting Data.mp4
MP4
35.8 MB
17. Handling Missing Values & Feature Engineering.mp4
MP4
25.8 MB
18. Train-Test Split & Scaling Normalization.mp4
MP4
19.2 MB
5 - Exploratory Data Analysis (EDA)
19. Understanding Your Data.mp4
MP4
9.4 MB
20. Summary Statistics.mp4
MP4
10.7 MB
21. Data Visualisation Basics.mp4
MP4
19.3 MB
22. Scatter Plots & Bar Charts.mp4
MP4
13.4 MB
23. Correlation Analysis.mp4
MP4
19.1 MB
24. Distribution Plots.mp4
MP4
8.6 MB
6 - Supervised Learning - Regression
25. Understanding Regression Simple Linear Regression & Multiple Linear Regression.mp4
MP4
31.4 MB
26. Model Training & Evaluation.mp4
MP4
27.4 MB
27. MAE(Mean Absolute Error), MSE(Mean Squared Error), RMSE(Root Mean Squared Error).mp4
MP4
10.9 MB
7 - Supervised Learning - Classification
28. Logistic Regression.mp4
MP4
25.6 MB
29. K-Nearest Neighbors.mp4
MP4
36.6 MB
20 matching files shown out of 29 matching files, 66 total files.
  • Seeders: 25
  • Leechers: 14
  • Size: 992.3 MB
  • Files: 66
  • Age: 4 months ago
file_upload 66
storage 992.3 MB
access_time 4 months ago
~Get Your Files Here !
1 - Introduction
Logistic Regression in Python
Data Files
Others
Presentation
10 - Knearest Neighbors Classifier
11 - Understanding The Results
12 - Appendix 1 Linear Regression In Python
ML Practical task 3
ML Task 1
ML Task 2
13 - Congratulations About Your Certificate
2 - Introduction To Machine Learning
3 - Basics Of Statistics
4 - Setting Up Python And Jupyter Notebook
5 - Important Python Libraries
21 - Working With Numpy Library Of Python.mp4
MP4
52.9 MB
22 - Working With Pandas Library Of Python.mp4
MP4
55.9 MB
23 - Working With Seaborn Library Of Python.mp4
MP4
61.7 MB
6 - Data Preprocessing
26 - Gathering Business Knowledge.mp4
MP4
8.7 MB
27 - Data Exploration.mp4
MP4
14.6 MB
28 - The Dataset And The Data Dictionary.mp4
MP4
127.4 MB
29 - Data Import In Python.mp4
MP4
35.5 MB
31 - Univariate Analysis And Edd.mp4
MP4
19 MB
32 - Edd In Python.mp4
MP4
123.8 MB
34 - Outlier Treatment.mp4
MP4
16.2 MB
35 - Outlier Treatment In Python.mp4
MP4
76.5 MB
37 - Missing Value Imputation.mp4
MP4
15.4 MB
38 - Missing Value Imputation In Python.mp4
MP4
34.5 MB
40 - Seasonality In Data.mp4
MP4
12.3 MB
41 - Variable Transformation.mp4
MP4
22.1 MB
42 - Variable Transformation And Deletion In Python.mp4
MP4
39.9 MB
44 - Dummy Variable Creation Handling Qualitative Data.mp4
MP4
21.7 MB
45 - Dummy Variable Creation In Python.mp4
MP4
43.7 MB
7 - Classification Models
47 - Three Classifiers And The Problem Statement.mp4
MP4
31.8 MB
48 - Why Cant We Use Linear Regression.mp4
MP4
28 MB
20 matching files shown out of 33 matching files, 151 total files.
  • Seeders: 2
  • Leechers: 5
  • Size: 3 GB
  • Files: 151
  • Age: 1 month ago
file_upload 151
storage 3 GB
access_time 1 month ago
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