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| 10 - Pandas Introduction and Installation.mp4 |
24.82Мб |
| 11 - Pandas-Series.ipynb |
1.54Кб |
| 11 - Pandas Series.mp4 |
17.01Мб |
| 12 - Pandas DataFrame.mp4 |
25.23Мб |
| 12 - Pandas-DataFrame-Practical.ipynb |
3.19Кб |
| 13 - Pandas ReadCSV.mp4 |
17.90Мб |
| 13 - Read-CSV.ipynb |
17.25Кб |
| 14 - Analyzing-DataFrames.ipynb |
60.11Кб |
| 14 - Pandas Analyzing DataFrames.mp4 |
46.05Мб |
| 15 - Matplotlib-Intro-and-Getting-started.ipynb |
15.15Кб |
| 15 - Matplotlib Introduction.mp4 |
27.31Мб |
| 16 - Different-types-of-plots-in-Matplotlib.ipynb |
29.33Кб |
| 16 - Different types of plots in Matplotlib.mp4 |
43.67Мб |
| 17 - Seaborn.mp4 |
60.34Мб |
| 18 - Handling Missing Values.mp4 |
62.02Мб |
| 18 - Handling-Missing-Values-1.pptx |
620.89Кб |
| 18 - Missing-Values.ipynb |
14.91Кб |
| 19 - Feature-Encoding.ipynb |
36.83Кб |
| 19 - Feature Encoding.mp4 |
64.44Мб |
| 19 - Feature-Encoding.pptx |
492.31Кб |
| 1 - Welcome.mp4 |
21.02Мб |
| 1 - Welcome-to-the-Course.pptx |
287.39Кб |
| 20 - Feature-Scaling.ipynb |
117.33Кб |
| 20 - Feature Scaling.mp4 |
54.08Мб |
| 21 - Machine Learning Introduction.mp4 |
35.25Мб |
| 22 - Supervised Machine Learning.mp4 |
26.29Мб |
| 23 - Unsupervised Machine Learning.mp4 |
21.61Мб |
| 24 - Train Test Split.mp4 |
13.87Мб |
| 25 - Regression Analysis.mp4 |
53.52Мб |
| 26 - Linear-Regression.ipynb |
22.04Кб |
| 26 - Linear Regression.mp4 |
49.59Мб |
| 26 - Linear-Regression.pptx |
360.12Кб |
| 26 - Salary-Data.csv |
454б |
| 27 - Logistic Regression.mp4 |
71.54Мб |
| 27 - Logistic-Regression.pptx |
405.18Кб |
| 27 - Logistic-Regression-Practical.ipynb |
25.33Кб |
| 28 - K-Nearest-Neighbors-KNN.pptx |
519.80Кб |
| 28 - KNN.mp4 |
75.27Мб |
| 28 - KNN-Practical.ipynb |
60.80Кб |
| 28 - User-Data.csv |
10.67Кб |
| 29 - Support-Vector-Machine-SVM.pptx |
554.79Кб |
| 29 - SVM.mp4 |
60.94Мб |
| 29 - SVM-Practical.ipynb |
8.68Кб |
| 29 - User-Data.csv |
10.67Кб |
| 2 - Course Overview.mp4 |
32.43Мб |
| 2 - Course-Overview.pptx |
291.87Кб |
| 30 - Decision Tree.mp4 |
70.83Мб |
| 30 - Decision-Tree-Algorithm.pptx |
463.37Кб |
| 30 - Decision-Tree-Practical.ipynb |
6.37Кб |
| 30 - User-Data.csv |
10.67Кб |
| 31 - Random Forest.mp4 |
46.36Мб |
| 31 - Random-Forest-Algorithm.pptx |
400.85Кб |
| 31 - Random-Forest-Practical.ipynb |
6.66Кб |
| 31 - User-Data.csv |
10.67Кб |
| 32 - K Means Clustering.mp4 |
63.07Мб |
| 32 - K-Means-Clustering-Algorithm.pptx |
588.47Кб |
| 32 - K-Means-Practical.ipynb |
60.72Кб |
| 32 - Mall-Customers.csv |
4.67Кб |
| 33 - GridSearch-CV.ipynb |
5.58Кб |
| 33 - GridSearch CV.mp4 |
70.43Мб |
| 33 - GridSearchCV.pptx |
487.17Кб |
| 34 - Machine Learning Pipeline.mp4 |
54.35Мб |
| 34 - Machine-learning-Pipeline.pptx |
415.53Кб |
| 34 - ML-Pipeline.ipynb |
10.54Кб |
| 35 - diabetes.csv |
23.31Кб |
| 35 - Diabetes Prediction.mp4 |
75.45Мб |
| 35 - Diabetes-Prediction-Project.ipynb |
27.57Кб |
| 36 - insurance.csv |
54.32Кб |
| 36 - Insurance Cost Prediction.mp4 |
79.79Мб |
| 36 - Medical-Insurance-Cost-Prediction.ipynb |
79.93Кб |
| 3 - Numpy Introduction and Installation.mp4 |
33.68Мб |
| 4 - Creating Arrays in Numpy.mp4 |
49.49Мб |
| 4 - Creating-Arrays-Numpy.ipynb |
4.49Кб |
| 5 - Array Shape and Reshape.mp4 |
47.11Мб |
| 5 - Shape-and-Reshape.ipynb |
5.23Кб |
| 6 - Array-Indexing.ipynb |
3.96Кб |
| 6 - Array Indexing.mp4 |
33.52Мб |
| 7 - Array Iterating.mp4 |
24.08Мб |
| 7 - Array-Iterating-Practical.ipynb |
2.11Кб |
| 8 - Array-Slicing.ipynb |
4.26Кб |
| 8 - Array Slicing.mp4 |
39.96Мб |
| 9 - Searching and Sorting.mp4 |
30.62Мб |
| 9 - Searching-and-Sorting-numpy-array-prac.ipynb |
3.94Кб |
| Bonus Resources.txt |
386б |
| Get Bonus Downloads Here.url |
182б |