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[GigaCourse.Com] Udemy - Machine Learning & Deep Learning in Python & R
大小 12.55 GB
文件数 539
Info Hash: 3ADEC4CA542730DF24B2184E3C5DEAEE6E240A56
收录时间 2025-12-15 07:22:47
更新时间 2025-12-15 07:22:47
文件列表 (539)
0. Websites you may like/[CourseClub.Me].url
122 B
0. Websites you may like/[GigaCourse.Com].url
49 B
1. Introduction/1. Introduction.mp4
29.39 MB
1. Introduction/1. Introduction.srt
4.64 KB
1. Introduction/2. Course Resources.html
370 B
10. Linear Discriminant Analysis (LDA)/1. Linear Discriminant Analysis.mp4
40.96 MB
10. Linear Discriminant Analysis (LDA)/1. Linear Discriminant Analysis.srt
12.29 KB
10. Linear Discriminant Analysis (LDA)/2. LDA in Python.mp4
11.4 MB
10. Linear Discriminant Analysis (LDA)/2. LDA in Python.srt
2.58 KB
10. Linear Discriminant Analysis (LDA)/3. Linear Discriminant Analysis in R.mp4
74.35 MB
10. Linear Discriminant Analysis (LDA)/3. Linear Discriminant Analysis in R.srt
10.5 KB
11. K-Nearest Neighbors classifier/1. Test-Train Split.mp4
39.3 MB
11. K-Nearest Neighbors classifier/1. Test-Train Split.srt
10.97 KB
11. K-Nearest Neighbors classifier/2. Test-Train Split in Python.mp4
33.1 MB
11. K-Nearest Neighbors classifier/2. Test-Train Split in Python.srt
7.6 KB
11. K-Nearest Neighbors classifier/3. Test-Train Split in R.mp4
74.23 MB
11. K-Nearest Neighbors classifier/3. Test-Train Split in R.srt
10.27 KB
11. K-Nearest Neighbors classifier/4. K-Nearest Neighbors classifier.mp4
75.42 MB
11. K-Nearest Neighbors classifier/4. K-Nearest Neighbors classifier.srt
10.33 KB
11. K-Nearest Neighbors classifier/5. K-Nearest Neighbors in Python Part 1.mp4
37.23 MB
11. K-Nearest Neighbors classifier/5. K-Nearest Neighbors in Python Part 1.srt
5.85 KB
11. K-Nearest Neighbors classifier/6. K-Nearest Neighbors in Python Part 2.mp4
42.36 MB
11. K-Nearest Neighbors classifier/6. K-Nearest Neighbors in Python Part 2.srt
6.9 KB
11. K-Nearest Neighbors classifier/7. K-Nearest Neighbors in R.mp4
64.85 MB
11. K-Nearest Neighbors classifier/7. K-Nearest Neighbors in R.srt
9.36 KB
12. Comparing results from 3 models/1. Understanding the results of classification models.mp4
41.64 MB
12. Comparing results from 3 models/1. Understanding the results of classification models.srt
7.8 KB
12. Comparing results from 3 models/2. Summary of the three models.mp4
22.21 MB
12. Comparing results from 3 models/2. Summary of the three models.srt
6.2 KB
13. Simple Decision Trees/1. Introduction to Decision trees.mp4
44.78 MB
13. Simple Decision Trees/1. Introduction to Decision trees.srt
4.74 KB
13. Simple Decision Trees/10. Test-Train split in Python.mp4
25.62 MB
13. Simple Decision Trees/10. Test-Train split in Python.srt
5.29 KB
13. Simple Decision Trees/11. Splitting Data into Test and Train Set in R.mp4
43.97 MB
13. Simple Decision Trees/11. Splitting Data into Test and Train Set in R.srt
7.29 KB
13. Simple Decision Trees/12. Creating Decision tree in Python.mp4
17.87 MB
13. Simple Decision Trees/12. Creating Decision tree in Python.srt
4.34 KB
13. Simple Decision Trees/13. Building a Regression Tree in R.mp4
103.33 MB
13. Simple Decision Trees/13. Building a Regression Tree in R.srt
18.88 KB
13. Simple Decision Trees/14. Evaluating model performance in Python.mp4
16.44 MB
13. Simple Decision Trees/14. Evaluating model performance in Python.srt
4.81 KB
13. Simple Decision Trees/15. Plotting decision tree in Python.mp4
21.48 MB
13. Simple Decision Trees/15. Plotting decision tree in Python.srt
5.48 KB
13. Simple Decision Trees/16. Pruning a tree.mp4
18.46 MB
13. Simple Decision Trees/16. Pruning a tree.srt
5.42 KB
13. Simple Decision Trees/17. Pruning a tree in Python.mp4
73.5 MB
13. Simple Decision Trees/17. Pruning a tree in Python.srt
11.06 KB
13. Simple Decision Trees/18. Pruning a Tree in R.mp4
82.09 MB
13. Simple Decision Trees/18. Pruning a Tree in R.srt
11.8 KB
13. Simple Decision Trees/2. Basics of Decision Trees.mp4
42.65 MB
13. Simple Decision Trees/2. Basics of Decision Trees.srt
13.19 KB
13. Simple Decision Trees/3. Understanding a Regression Tree.mp4
43.73 MB
13. Simple Decision Trees/3. Understanding a Regression Tree.srt
13.97 KB
13. Simple Decision Trees/4. The stopping criteria for controlling tree growth.mp4
13.97 MB
13. Simple Decision Trees/4. The stopping criteria for controlling tree growth.srt
4.29 KB
13. Simple Decision Trees/5. Importing the Data set into Python.mp4
15.86 MB
13. Simple Decision Trees/5. Importing the Data set into Python.srt
3.12 KB
13. Simple Decision Trees/6. Importing the Data set into R.mp4
43.7 MB
13. Simple Decision Trees/6. Importing the Data set into R.srt
8.75 KB
13. Simple Decision Trees/7. Missing value treatment in Python.mp4
12.94 MB
13. Simple Decision Trees/7. Missing value treatment in Python.srt
2.32 KB
13. Simple Decision Trees/8. Dummy Variable creation in Python.mp4
24.57 MB
13. Simple Decision Trees/8. Dummy Variable creation in Python.srt
4.49 KB
13. Simple Decision Trees/9. Dependent- Independent Data split in Python.mp4
16.87 MB
13. Simple Decision Trees/9. Dependent- Independent Data split in Python.srt
3.82 KB
14. Simple Classification Tree/1. Classification tree.mp4
28.2 MB
14. Simple Classification Tree/1. Classification tree.srt
8.11 KB
14. Simple Classification Tree/2. The Data set for Classification problem.mp4
18.57 MB
14. Simple Classification Tree/2. The Data set for Classification problem.srt
2.36 KB
14. Simple Classification Tree/3. Classification tree in Python Preprocessing.mp4
45.39 MB
14. Simple Classification Tree/3. Classification tree in Python Preprocessing.srt
9.15 KB
14. Simple Classification Tree/4. Classification tree in Python Training.mp4
82.71 MB
14. Simple Classification Tree/4. Classification tree in Python Training.srt
14.88 KB
14. Simple Classification Tree/5. Building a classification Tree in R.mp4
85.11 MB
14. Simple Classification Tree/5. Building a classification Tree in R.srt
11.88 KB
14. Simple Classification Tree/6. Advantages and Disadvantages of Decision Trees.mp4
6.86 MB
14. Simple Classification Tree/6. Advantages and Disadvantages of Decision Trees.srt
2.16 KB
15. Ensemble technique 1 - Bagging/1. Ensemble technique 1 - Bagging.mp4
28.14 MB
15. Ensemble technique 1 - Bagging/1. Ensemble technique 1 - Bagging.srt
7.58 KB
15. Ensemble technique 1 - Bagging/2. Ensemble technique 1 - Bagging in Python.mp4
77.31 MB
15. Ensemble technique 1 - Bagging/2. Ensemble technique 1 - Bagging in Python.srt
12.61 KB
15. Ensemble technique 1 - Bagging/3. Bagging in R.mp4
58.96 MB
15. Ensemble technique 1 - Bagging/3. Bagging in R.srt
8.16 KB
16. Ensemble technique 2 - Random Forests/1. Ensemble technique 2 - Random Forests.mp4
18.2 MB
16. Ensemble technique 2 - Random Forests/1. Ensemble technique 2 - Random Forests.srt
5.07 KB
16. Ensemble technique 2 - Random Forests/2. Ensemble technique 2 - Random Forests in Python.mp4
46.7 MB
16. Ensemble technique 2 - Random Forests/2. Ensemble technique 2 - Random Forests in Python.srt
6.9 KB
16. Ensemble technique 2 - Random Forests/3. Using Grid Search in Python.mp4
80.66 MB
16. Ensemble technique 2 - Random Forests/3. Using Grid Search in Python.srt
14.05 KB
16. Ensemble technique 2 - Random Forests/4. Random Forest in R.mp4
30.72 MB
16. Ensemble technique 2 - Random Forests/4. Random Forest in R.srt
5.58 KB
17. Ensemble technique 3 - Boosting/1. Boosting.mp4
30.58 MB
17. Ensemble technique 3 - Boosting/1. Boosting.srt
9.58 KB
17. Ensemble technique 3 - Boosting/2. Ensemble technique 3a - Boosting in Python.mp4
39.87 MB
17. Ensemble technique 3 - Boosting/2. Ensemble technique 3a - Boosting in Python.srt
5.61 KB
17. Ensemble technique 3 - Boosting/3. Gradient Boosting in R.mp4
69.09 MB
17. Ensemble technique 3 - Boosting/3. Gradient Boosting in R.srt
9.62 KB
17. Ensemble technique 3 - Boosting/4. Ensemble technique 3b - AdaBoost in Python.mp4
30.53 MB
17. Ensemble technique 3 - Boosting/4. Ensemble technique 3b - AdaBoost in Python.srt
4.55 KB
17. Ensemble technique 3 - Boosting/5. AdaBoosting in R.mp4
88.68 MB
17. Ensemble technique 3 - Boosting/5. AdaBoosting in R.srt
12.24 KB
17. Ensemble technique 3 - Boosting/6. Ensemble technique 3c - XGBoost in Python.mp4
75 MB
17. Ensemble technique 3 - Boosting/6. Ensemble technique 3c - XGBoost in Python.srt
11.63 KB
17. Ensemble technique 3 - Boosting/7. XGBoosting in R.mp4
161.3 MB
17. Ensemble technique 3 - Boosting/7. XGBoosting in R.srt
21.1 KB
18. Support Vector Machines/1. Introduction to SVM's.mp4
21.62 MB
18. Support Vector Machines/1. Introduction to SVM's.srt
3.26 KB
18. Support Vector Machines/2. The Concept of a Hyperplane.mp4
29.42 MB
18. Support Vector Machines/2. The Concept of a Hyperplane.srt
6.22 KB
18. Support Vector Machines/3. Maximum Margin Classifier.mp4
22.49 MB
18. Support Vector Machines/3. Maximum Margin Classifier.srt
4.41 KB
18. Support Vector Machines/4. Limitations of Maximum Margin Classifier.mp4
10.6 MB
18. Support Vector Machines/4. Limitations of Maximum Margin Classifier.srt
3.12 KB
19. Support Vector Classifier/1. Support Vector classifiers.mp4
56.16 MB
19. Support Vector Classifier/1. Support Vector classifiers.srt
12.46 KB
19. Support Vector Classifier/2. Limitations of Support Vector Classifiers.mp4
10.81 MB
19. Support Vector Classifier/2. Limitations of Support Vector Classifiers.srt
1.9 KB
2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp4
16.27 MB
2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.srt
2.67 KB
2. Setting up Python and Jupyter Notebook/10. Working with Seaborn Library of Python.mp4
40.37 MB
2. Setting up Python and Jupyter Notebook/10. Working with Seaborn Library of Python.srt
9.08 KB
2. Setting up Python and Jupyter Notebook/2. This is a milestone!.mp4
20.66 MB
2. Setting up Python and Jupyter Notebook/2. This is a milestone!.srt
3.94 KB
2. Setting up Python and Jupyter Notebook/3. Opening Jupyter Notebook.mp4
65.19 MB
2. Setting up Python and Jupyter Notebook/3. Opening Jupyter Notebook.srt
10.08 KB
2. Setting up Python and Jupyter Notebook/4. Introduction to Jupyter.mp4
40.91 MB
2. Setting up Python and Jupyter Notebook/4. Introduction to Jupyter.srt
15.54 KB
2. Setting up Python and Jupyter Notebook/5. Arithmetic operators in Python Python Basics.mp4
12.74 MB
2. Setting up Python and Jupyter Notebook/5. Arithmetic operators in Python Python Basics.srt
4.62 KB
2. Setting up Python and Jupyter Notebook/6. Strings in Python Python Basics.mp4
64.43 MB
2. Setting up Python and Jupyter Notebook/6. Strings in Python Python Basics.srt
18.58 KB
2. Setting up Python and Jupyter Notebook/7. Lists, Tuples and Directories Python Basics.mp4
60.32 MB
2. Setting up Python and Jupyter Notebook/7. Lists, Tuples and Directories Python Basics.srt
22.17 KB
2. Setting up Python and Jupyter Notebook/8. Working with Numpy Library of Python.mp4
43.87 MB
2. Setting up Python and Jupyter Notebook/8. Working with Numpy Library of Python.srt
12.84 KB
2. Setting up Python and Jupyter Notebook/9. Working with Pandas Library of Python.mp4
46.88 MB
2. Setting up Python and Jupyter Notebook/9. Working with Pandas Library of Python.srt
10.33 KB
20. Support Vector Machines/1. Kernel Based Support Vector Machines.mp4
40.12 MB
20. Support Vector Machines/1. Kernel Based Support Vector Machines.srt
8.46 KB
21. Creating Support Vector Machine Model in Python/1. Regression and Classification Models.mp4
4.03 MB
21. Creating Support Vector Machine Model in Python/1. Regression and Classification Models.srt
817 B
21. Creating Support Vector Machine Model in Python/10. Radial Kernel with Hyperparameter Tuning.mp4
37.21 MB
21. Creating Support Vector Machine Model in Python/10. Radial Kernel with Hyperparameter Tuning.srt
7.23 KB
21. Creating Support Vector Machine Model in Python/2. Importing and preprocessing data in Python.mp4
26.45 MB
21. Creating Support Vector Machine Model in Python/2. Importing and preprocessing data in Python.srt
4.51 KB
21. Creating Support Vector Machine Model in Python/3. Standardizing the data.mp4
38.41 MB
21. Creating Support Vector Machine Model in Python/3. Standardizing the data.srt
6.69 KB
21. Creating Support Vector Machine Model in Python/4. SVM based Regression Model in Python.mp4
67.63 MB
21. Creating Support Vector Machine Model in Python/4. SVM based Regression Model in Python.srt
10.64 KB
21. Creating Support Vector Machine Model in Python/5. Classification model - Preprocessing.mp4
45.37 MB
21. Creating Support Vector Machine Model in Python/5. Classification model - Preprocessing.srt
9.17 KB
21. Creating Support Vector Machine Model in Python/6. Classification model - Standardizing the data.mp4
9.72 MB
21. Creating Support Vector Machine Model in Python/6. Classification model - Standardizing the data.srt
1.94 KB
21. Creating Support Vector Machine Model in Python/7. SVM Based classification model.mp4
64.13 MB
21. Creating Support Vector Machine Model in Python/7. SVM Based classification model.srt
12.7 KB
21. Creating Support Vector Machine Model in Python/8. Hyper Parameter Tuning.mp4
57.74 MB
21. Creating Support Vector Machine Model in Python/8. Hyper Parameter Tuning.srt
10.91 KB
21. Creating Support Vector Machine Model in Python/9. Polynomial Kernel with Hyperparameter Tuning.mp4
22.92 MB
21. Creating Support Vector Machine Model in Python/9. Polynomial Kernel with Hyperparameter Tuning.srt
4.39 KB
22. Creating Support Vector Machine Model in R/1. Importing and preprocessing data in R.mp4
24.99 MB
22. Creating Support Vector Machine Model in R/1. Importing and preprocessing data in R.srt
2.81 KB
22. Creating Support Vector Machine Model in R/2. More about test-train split.html
559 B
22. Creating Support Vector Machine Model in R/3. Classification SVM model using Linear Kernel.mp4
139.16 MB
22. Creating Support Vector Machine Model in R/3. Classification SVM model using Linear Kernel.srt
18.39 KB
22. Creating Support Vector Machine Model in R/4. Hyperparameter Tuning for Linear Kernel.mp4
60.5 MB
22. Creating Support Vector Machine Model in R/4. Hyperparameter Tuning for Linear Kernel.srt
7.16 KB
22. Creating Support Vector Machine Model in R/5. Polynomial Kernel with Hyperparameter Tuning.mp4
83.14 MB
22. Creating Support Vector Machine Model in R/5. Polynomial Kernel with Hyperparameter Tuning.srt
11.84 KB
22. Creating Support Vector Machine Model in R/6. Radial Kernel with Hyperparameter Tuning.mp4
56.68 MB
22. Creating Support Vector Machine Model in R/6. Radial Kernel with Hyperparameter Tuning.srt
7.36 KB
22. Creating Support Vector Machine Model in R/7. SVM based Regression Model in R.mp4
106.13 MB
22. Creating Support Vector Machine Model in R/7. SVM based Regression Model in R.srt
12.51 KB
23. Introduction - Deep Learning/1. Introduction to Neural Networks and Course flow.mp4
29.07 MB
23. Introduction - Deep Learning/1. Introduction to Neural Networks and Course flow.srt
4.96 KB
23. Introduction - Deep Learning/2. Perceptron.mp4
44.76 MB
23. Introduction - Deep Learning/2. Perceptron.srt
10.69 KB
23. Introduction - Deep Learning/3. Activation Functions.mp4
34.61 MB
23. Introduction - Deep Learning/3. Activation Functions.srt
8.51 KB
23. Introduction - Deep Learning/4. Python - Creating Perceptron model.mp4
86.56 MB
23. Introduction - Deep Learning/4. Python - Creating Perceptron model.srt
16.21 KB
24. Neural Networks - Stacking cells to create network/1. Basic Terminologies.mp4
40.42 MB
24. Neural Networks - Stacking cells to create network/1. Basic Terminologies.srt
11.35 KB
24. Neural Networks - Stacking cells to create network/2. Gradient Descent.mp4
60.34 MB
24. Neural Networks - Stacking cells to create network/2. Gradient Descent.srt
13.24 KB
24. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4
122.2 MB
24. Neural Networks - Stacking cells to create network/3. Back Propagation.srt
25.88 KB
24. Neural Networks - Stacking cells to create network/4. Some Important Concepts.mp4
62.18 MB
24. Neural Networks - Stacking cells to create network/4. Some Important Concepts.srt
14.23 KB
24. Neural Networks - Stacking cells to create network/5. Hyperparameter.mp4
45.36 MB
24. Neural Networks - Stacking cells to create network/5. Hyperparameter.srt
9.66 KB
25. ANN in Python/1. Keras and Tensorflow.mp4
14.91 MB
25. ANN in Python/1. Keras and Tensorflow.srt
3.89 KB
25. ANN in Python/10. Using Functional API for complex architectures.mp4
92.1 MB
25. ANN in Python/10. Using Functional API for complex architectures.srt
13.37 KB
25. ANN in Python/11. Saving - Restoring Models and Using Callbacks.mp4
151.58 MB
25. ANN in Python/11. Saving - Restoring Models and Using Callbacks.srt
21.59 KB
25. ANN in Python/12. Hyperparameter Tuning.mp4
60.63 MB
25. ANN in Python/12. Hyperparameter Tuning.srt
10.17 KB
25. ANN in Python/2. Installing Tensorflow and Keras.mp4
20.06 MB
25. ANN in Python/2. Installing Tensorflow and Keras.srt
4.28 KB
25. ANN in Python/3. Dataset for classification.mp4
56.19 MB
25. ANN in Python/3. Dataset for classification.srt
8.16 KB
25. ANN in Python/4. Normalization and Test-Train split.mp4
44.2 MB
25. ANN in Python/4. Normalization and Test-Train split.srt
6.32 KB
25. ANN in Python/5. Different ways to create ANN using Keras.mp4
10.81 MB
25. ANN in Python/5. Different ways to create ANN using Keras.srt
2.02 KB
25. ANN in Python/6. Building the Neural Network using Keras.mp4
79.11 MB
25. ANN in Python/6. Building the Neural Network using Keras.srt
13.32 KB
25. ANN in Python/7. Compiling and Training the Neural Network model.mp4
81.63 MB
25. ANN in Python/7. Compiling and Training the Neural Network model.srt
10.37 KB
25. ANN in Python/8. Evaluating performance and Predicting using Keras.mp4
69.91 MB
25. ANN in Python/8. Evaluating performance and Predicting using Keras.srt
10.11 KB
25. ANN in Python/9. Building Neural Network for Regression Problem.mp4
155.91 MB
25. ANN in Python/9. Building Neural Network for Regression Problem.srt
24.71 KB
26. ANN in R/1. Installing Keras and Tensorflow.mp4
22.78 MB
26. ANN in R/1. Installing Keras and Tensorflow.srt
3.11 KB
26. ANN in R/2. Data Normalization and Test-Train Split.mp4
111.78 MB
26. ANN in R/2. Data Normalization and Test-Train Split.srt
13.36 KB
26. ANN in R/3. Building,Compiling and Training.mp4
130.73 MB
26. ANN in R/3. Building,Compiling and Training.srt
16.92 KB
26. ANN in R/4. Evaluating and Predicting.mp4
99.28 MB
26. ANN in R/4. Evaluating and Predicting.srt
10.52 KB
26. ANN in R/5. ANN with NeuralNets Package.mp4
84.42 MB
26. ANN in R/5. ANN with NeuralNets Package.srt
8.78 KB
26. ANN in R/6. Building Regression Model with Functional API.mp4
131.13 MB
26. ANN in R/6. Building Regression Model with Functional API.srt
14.16 KB
26. ANN in R/7. Complex Architectures using Functional API.mp4
79.57 MB
26. ANN in R/7. Complex Architectures using Functional API.srt
9.17 KB
26. ANN in R/8. Saving - Restoring Models and Using Callbacks.mp4
216.04 MB
26. ANN in R/8. Saving - Restoring Models and Using Callbacks.srt
22.28 KB
27. CNN - Basics/1. CNN Introduction.mp4
56.75 MB
27. CNN - Basics/1. CNN Introduction.srt
8.33 KB
27. CNN - Basics/2. Stride.mp4
16.59 MB
27. CNN - Basics/2. Stride.srt
3.11 KB
27. CNN - Basics/3. Padding.mp4
31.64 MB
27. CNN - Basics/3. Padding.srt
5.11 KB
27. CNN - Basics/4. Filters and Feature maps.mp4
52.71 MB
27. CNN - Basics/4. Filters and Feature maps.srt
7.87 KB
27. CNN - Basics/5. Channels.mp4
67.77 MB
27. CNN - Basics/5. Channels.srt
6.48 KB
27. CNN - Basics/6. PoolingLayer.mp4
46.87 MB
27. CNN - Basics/6. PoolingLayer.srt
6.12 KB
28. Creating CNN model in Python/1. CNN model in Python - Preprocessing.mp4
40.63 MB
28. Creating CNN model in Python/1. CNN model in Python - Preprocessing.srt
5.88 KB
28. Creating CNN model in Python/2. CNN model in Python - structure and Compile.mp4
43.26 MB
28. Creating CNN model in Python/2. CNN model in Python - structure and Compile.srt
7.53 KB
28. Creating CNN model in Python/3. CNN model in Python - Training and results.mp4
55.15 MB
28. Creating CNN model in Python/3. CNN model in Python - Training and results.srt
6.59 KB
28. Creating CNN model in Python/4. Comparison - Pooling vs Without Pooling in Python.mp4
57.97 MB
28. Creating CNN model in Python/4. Comparison - Pooling vs Without Pooling in Python.srt
5.77 KB
29. Creating CNN model in R/1. CNN on MNIST Fashion Dataset - Model Architecture.mp4
7.35 MB
29. Creating CNN model in R/1. CNN on MNIST Fashion Dataset - Model Architecture.srt
2.47 KB
29. Creating CNN model in R/2. Data Preprocessing.mp4
67.02 MB
29. Creating CNN model in R/2. Data Preprocessing.srt
7.76 KB
29. Creating CNN model in R/3. Creating Model Architecture.mp4
71.6 MB
29. Creating CNN model in R/3. Creating Model Architecture.srt
6.55 KB
29. Creating CNN model in R/4. Compiling and training.mp4
32.21 MB
29. Creating CNN model in R/4. Compiling and training.srt
3.27 KB
29. Creating CNN model in R/5. Model Performance.mp4
68.08 MB
29. Creating CNN model in R/5. Model Performance.srt
6.83 KB
29. Creating CNN model in R/6. Comparison - Pooling vs Without Pooling in R.mp4
44.6 MB
29. Creating CNN model in R/6. Comparison - Pooling vs Without Pooling in R.srt
4.31 KB
3. Setting up R Studio and R crash course/1. Installing R and R studio.mp4
35.71 MB
3. Setting up R Studio and R crash course/1. Installing R and R studio.srt
7.37 KB
3. Setting up R Studio and R crash course/2. Basics of R and R studio.mp4
38.84 MB
3. Setting up R Studio and R crash course/2. Basics of R and R studio.srt
14.35 KB
3. Setting up R Studio and R crash course/3. Packages in R.mp4
82.94 MB
3. Setting up R Studio and R crash course/3. Packages in R.srt
14.6 KB
3. Setting up R Studio and R crash course/4. Inputting data part 1 Inbuilt datasets of R.mp4
40.74 MB
3. Setting up R Studio and R crash course/4. Inputting data part 1 Inbuilt datasets of R.srt
5.61 KB
3. Setting up R Studio and R crash course/5. Inputting data part 2 Manual data entry.mp4
25.52 MB
3. Setting up R Studio and R crash course/5. Inputting data part 2 Manual data entry.srt
3.68 KB
3. Setting up R Studio and R crash course/6. Inputting data part 3 Importing from CSV or Text files.mp4
60.1 MB
3. Setting up R Studio and R crash course/6. Inputting data part 3 Importing from CSV or Text files.srt
8.38 KB
3. Setting up R Studio and R crash course/7. Creating Barplots in R.mp4
96.73 MB
3. Setting up R Studio and R crash course/7. Creating Barplots in R.srt
18.34 KB
3. Setting up R Studio and R crash course/8. Creating Histograms in R.mp4
42.02 MB
3. Setting up R Studio and R crash course/8. Creating Histograms in R.srt
7.58 KB
30. Project Creating CNN model from scratch in Python/1. Project - Introduction.mp4
49.39 MB
30. Project Creating CNN model from scratch in Python/1. Project - Introduction.srt
7.75 KB
30. Project Creating CNN model from scratch in Python/2. Data for the project.html
232 B
30. Project Creating CNN model from scratch in Python/3. Project - Data Preprocessing in Python.mp4
71.83 MB
30. Project Creating CNN model from scratch in Python/3. Project - Data Preprocessing in Python.srt
9.44 KB
30. Project Creating CNN model from scratch in Python/4. Project - Training CNN model in Python.mp4
65.98 MB
30. Project Creating CNN model from scratch in Python/4. Project - Training CNN model in Python.srt
9.39 KB
30. Project Creating CNN model from scratch in Python/5. Project in Python - model results.mp4
21.02 MB
30. Project Creating CNN model from scratch in Python/5. Project in Python - model results.srt
2.95 KB
31. Project Creating CNN model from scratch/1. Project in R - Data Preprocessing.mp4
87.76 MB
31. Project Creating CNN model from scratch/1. Project in R - Data Preprocessing.srt
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31. Project Creating CNN model from scratch/2. CNN Project in R - Structure and Compile.mp4
46.11 MB
31. Project Creating CNN model from scratch/2. CNN Project in R - Structure and Compile.srt
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31. Project Creating CNN model from scratch/3. Project in R - Training.mp4
24.59 MB
31. Project Creating CNN model from scratch/3. Project in R - Training.srt
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31. Project Creating CNN model from scratch/4. Project in R - Model Performance.mp4
23.18 MB
31. Project Creating CNN model from scratch/4. Project in R - Model Performance.srt
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31. Project Creating CNN model from scratch/5. Project in R - Data Augmentation.mp4
56.38 MB
31. Project Creating CNN model from scratch/5. Project in R - Data Augmentation.srt
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31. Project Creating CNN model from scratch/6. Project in R - Validation Performance.mp4
23.69 MB
31. Project Creating CNN model from scratch/6. Project in R - Validation Performance.srt
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32. Project Data Augmentation for avoiding overfitting/1. Project - Data Augmentation Preprocessing.mp4
41.41 MB
32. Project Data Augmentation for avoiding overfitting/1. Project - Data Augmentation Preprocessing.srt
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32. Project Data Augmentation for avoiding overfitting/2. Project - Data Augmentation Training and Results.mp4
53.05 MB
32. Project Data Augmentation for avoiding overfitting/2. Project - Data Augmentation Training and Results.srt
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33. Transfer Learning Basics/1. ILSVRC.mp4
20.92 MB
33. Transfer Learning Basics/1. ILSVRC.srt
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33. Transfer Learning Basics/2. LeNET.mp4
7 MB
33. Transfer Learning Basics/2. LeNET.srt
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33. Transfer Learning Basics/3. VGG16NET.mp4
10.35 MB
33. Transfer Learning Basics/3. VGG16NET.srt
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33. Transfer Learning Basics/4. GoogLeNet.mp4
21.37 MB
33. Transfer Learning Basics/4. GoogLeNet.srt
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33. Transfer Learning Basics/5. Transfer Learning.mp4
29.99 MB
33. Transfer Learning Basics/5. Transfer Learning.srt
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33. Transfer Learning Basics/6. Project - Transfer Learning - VGG16.mp4
129.09 MB
33. Transfer Learning Basics/6. Project - Transfer Learning - VGG16.srt
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34. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).mp4
101.58 MB
34. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).srt
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34. Transfer Learning in R/2. Project - Transfer Learning - VGG16 (Performance).mp4
64.12 MB
34. Transfer Learning in R/2. Project - Transfer Learning - VGG16 (Performance).srt
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35. Time Series Analysis and Forecasting/1. Introduction.mp4
18.68 MB
35. Time Series Analysis and Forecasting/1. Introduction.srt
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35. Time Series Analysis and Forecasting/2. Time Series Forecasting - Use cases.mp4
25.91 MB
35. Time Series Analysis and Forecasting/2. Time Series Forecasting - Use cases.srt
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35. Time Series Analysis and Forecasting/3. Forecasting model creation - Steps.mp4
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35. Time Series Analysis and Forecasting/3. Forecasting model creation - Steps.srt
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35. Time Series Analysis and Forecasting/4. Forecasting model creation - Steps 1 (Goal).mp4
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35. Time Series Analysis and Forecasting/4. Forecasting model creation - Steps 1 (Goal).srt
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35. Time Series Analysis and Forecasting/5. Time Series - Basic Notations.mp4
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35. Time Series Analysis and Forecasting/5. Time Series - Basic Notations.srt
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36. Time Series - Preprocessing in Python/1. Data Loading in Python.mp4
108.86 MB
36. Time Series - Preprocessing in Python/1. Data Loading in Python.srt
18.51 KB
36. Time Series - Preprocessing in Python/10. Exponential Smoothing.mp4
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36. Time Series - Preprocessing in Python/10. Exponential Smoothing.srt
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36. Time Series - Preprocessing in Python/2. Time Series - Visualization Basics.mp4
63.72 MB
36. Time Series - Preprocessing in Python/2. Time Series - Visualization Basics.srt
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36. Time Series - Preprocessing in Python/3. Time Series - Visualization in Python.mp4
165.19 MB
36. Time Series - Preprocessing in Python/3. Time Series - Visualization in Python.srt
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36. Time Series - Preprocessing in Python/4. Time Series - Feature Engineering Basics.mp4
59.47 MB
36. Time Series - Preprocessing in Python/4. Time Series - Feature Engineering Basics.srt
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36. Time Series - Preprocessing in Python/5. Time Series - Feature Engineering in Python.mp4
112.69 MB
36. Time Series - Preprocessing in Python/5. Time Series - Feature Engineering in Python.srt
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36. Time Series - Preprocessing in Python/6. Time Series - Upsampling and Downsampling.mp4
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36. Time Series - Preprocessing in Python/6. Time Series - Upsampling and Downsampling.srt
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36. Time Series - Preprocessing in Python/7. Time Series - Upsampling and Downsampling in Python.mp4
100.67 MB
36. Time Series - Preprocessing in Python/7. Time Series - Upsampling and Downsampling in Python.srt
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36. Time Series - Preprocessing in Python/8. Time Series - Power Transformation.mp4
14.85 MB
36. Time Series - Preprocessing in Python/8. Time Series - Power Transformation.srt
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36. Time Series - Preprocessing in Python/9. Moving Average.mp4
38.7 MB
36. Time Series - Preprocessing in Python/9. Moving Average.srt
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37. Time Series - Important Concepts/1. White Noise.mp4
11.37 MB
37. Time Series - Important Concepts/1. White Noise.srt
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37. Time Series - Important Concepts/2. Random Walk.mp4
21.16 MB
37. Time Series - Important Concepts/2. Random Walk.srt
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37. Time Series - Important Concepts/3. Decomposing Time Series in Python.mp4
59.84 MB
37. Time Series - Important Concepts/3. Decomposing Time Series in Python.srt
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37. Time Series - Important Concepts/4. Differencing.mp4
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37. Time Series - Important Concepts/4. Differencing.srt
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37. Time Series - Important Concepts/5. Differencing in Python.mp4
113 MB
37. Time Series - Important Concepts/5. Differencing in Python.srt
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38. Time Series - Implementation in Python/1. Test Train Split in Python.mp4
57.41 MB
38. Time Series - Implementation in Python/1. Test Train Split in Python.srt
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38. Time Series - Implementation in Python/2. Naive (Persistence) model in Python.mp4
43.37 MB
38. Time Series - Implementation in Python/2. Naive (Persistence) model in Python.srt
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38. Time Series - Implementation in Python/3. Auto Regression Model - Basics.mp4
16.89 MB
38. Time Series - Implementation in Python/3. Auto Regression Model - Basics.srt
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38. Time Series - Implementation in Python/4. Auto Regression Model creation in Python.mp4
53.49 MB
38. Time Series - Implementation in Python/4. Auto Regression Model creation in Python.srt
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38. Time Series - Implementation in Python/5. Auto Regression with Walk Forward validation in Python.mp4
49.59 MB
38. Time Series - Implementation in Python/5. Auto Regression with Walk Forward validation in Python.srt
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38. Time Series - Implementation in Python/6. Moving Average model -Basics.mp4
24.1 MB
38. Time Series - Implementation in Python/6. Moving Average model -Basics.srt
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38. Time Series - Implementation in Python/7. Moving Average model in Python.mp4
56.66 MB
38. Time Series - Implementation in Python/7. Moving Average model in Python.srt
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39. Time Series - ARIMA model/1. ACF and PACF.mp4
41.23 MB
39. Time Series - ARIMA model/1. ACF and PACF.srt
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39. Time Series - ARIMA model/2. ARIMA model - Basics.mp4
21.36 MB
39. Time Series - ARIMA model/2. ARIMA model - Basics.srt
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39. Time Series - ARIMA model/3. ARIMA model in Python.mp4
74.43 MB
39. Time Series - ARIMA model/3. ARIMA model in Python.srt
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39. Time Series - ARIMA model/4. ARIMA model with Walk Forward Validation in Python.mp4
32.15 MB
39. Time Series - ARIMA model/4. ARIMA model with Walk Forward Validation in Python.srt
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4. Basics of Statistics/1. Types of Data.mp4
21.77 MB
4. Basics of Statistics/1. Types of Data.srt
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4. Basics of Statistics/2. Types of Statistics.mp4
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4. Basics of Statistics/2. Types of Statistics.srt
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4. Basics of Statistics/3. Describing data Graphically.mp4
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4. Basics of Statistics/4. Measures of Centers.mp4
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4. Basics of Statistics/4. Measures of Centers.srt
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4. Basics of Statistics/5. Measures of Dispersion.mp4
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4. Basics of Statistics/5. Measures of Dispersion.srt
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40. Time Series - SARIMA model/1. SARIMA model.mp4
39.02 MB
40. Time Series - SARIMA model/1. SARIMA model.srt
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40. Time Series - SARIMA model/2. SARIMA model in Python.mp4
66.23 MB
40. Time Series - SARIMA model/2. SARIMA model in Python.srt
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40. Time Series - SARIMA model/3. Stationary time Series.mp4
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40. Time Series - SARIMA model/3. Stationary time Series.srt
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40. Time Series - SARIMA model/4. The final milestone!.mp4
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40. Time Series - SARIMA model/4. The final milestone!.srt
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41. Congratulations & About your certificate/1. Bonus Lecture.html
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5. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4
109.17 MB
5. Introduction to Machine Learning/1. Introduction to Machine Learning.srt
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5. Introduction to Machine Learning/2. Building a Machine Learning Model.mp4
39.48 MB
5. Introduction to Machine Learning/2. Building a Machine Learning Model.srt
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6. Data Preprocessing/1. Gathering Business Knowledge.mp4
14.52 MB
6. Data Preprocessing/1. Gathering Business Knowledge.srt
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6. Data Preprocessing/10. Outlier Treatment in Python.mp4
70.25 MB
6. Data Preprocessing/10. Outlier Treatment in Python.srt
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6. Data Preprocessing/11. Outlier Treatment in R.mp4
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6. Data Preprocessing/11. Outlier Treatment in R.srt
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6. Data Preprocessing/12. Missing Value Imputation.mp4
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6. Data Preprocessing/12. Missing Value Imputation.srt
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6. Data Preprocessing/13. Missing Value Imputation in Python.mp4
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6. Data Preprocessing/13. Missing Value Imputation in Python.srt
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6. Data Preprocessing/14. Missing Value imputation in R.mp4
26 MB
6. Data Preprocessing/14. Missing Value imputation in R.srt
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6. Data Preprocessing/15. Seasonality in Data.mp4
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6. Data Preprocessing/15. Seasonality in Data.srt
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6. Data Preprocessing/16. Bi-variate analysis and Variable transformation.mp4
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6. Data Preprocessing/16. Bi-variate analysis and Variable transformation.srt
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6. Data Preprocessing/17. Variable transformation and deletion in Python.mp4
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6. Data Preprocessing/17. Variable transformation and deletion in Python.srt
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6. Data Preprocessing/18. Variable transformation in R.mp4
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6. Data Preprocessing/18. Variable transformation in R.srt
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6. Data Preprocessing/19. Non-usable variables.mp4
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6. Data Preprocessing/19. Non-usable variables.srt
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6. Data Preprocessing/2. Data Exploration.mp4
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6. Data Preprocessing/2. Data Exploration.srt
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6. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp4
36.8 MB
6. Data Preprocessing/20. Dummy variable creation Handling qualitative data.srt
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6. Data Preprocessing/21. Dummy variable creation in Python.mp4
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6. Data Preprocessing/21. Dummy variable creation in Python.srt
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6. Data Preprocessing/22. Dummy variable creation in R.mp4
43.98 MB
6. Data Preprocessing/22. Dummy variable creation in R.srt
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6. Data Preprocessing/23. Correlation Analysis.mp4
71.6 MB
6. Data Preprocessing/23. Correlation Analysis.srt
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6. Data Preprocessing/24. Correlation Analysis in Python.mp4
55.3 MB
6. Data Preprocessing/24. Correlation Analysis in Python.srt
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6. Data Preprocessing/25. Correlation Matrix in R.mp4
83.14 MB
6. Data Preprocessing/25. Correlation Matrix in R.srt
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6. Data Preprocessing/26. Quiz.html
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6. Data Preprocessing/3. The Dataset and the Data Dictionary.mp4
69.28 MB
6. Data Preprocessing/3. The Dataset and the Data Dictionary.srt
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6. Data Preprocessing/4. Importing Data in Python.mp4
27.84 MB
6. Data Preprocessing/4. Importing Data in Python.srt
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6. Data Preprocessing/5. Importing the dataset into R.mp4
13.11 MB
6. Data Preprocessing/5. Importing the dataset into R.srt
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6. Data Preprocessing/6. Univariate analysis and EDD.mp4
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6. Data Preprocessing/6. Univariate analysis and EDD.srt
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6. Data Preprocessing/7. EDD in Python.mp4
61.8 MB
6. Data Preprocessing/7. EDD in Python.srt
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6. Data Preprocessing/8. EDD in R.mp4
96.98 MB
6. Data Preprocessing/8. EDD in R.srt
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6. Data Preprocessing/9. Outlier Treatment.mp4
27.26 MB
6. Data Preprocessing/9. Outlier Treatment.srt
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7. Linear Regression/1. The Problem Statement.mp4
9.38 MB
7. Linear Regression/1. The Problem Statement.srt
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7. Linear Regression/10. Multiple Linear Regression in Python.mp4
69.73 MB
7. Linear Regression/10. Multiple Linear Regression in Python.srt
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7. Linear Regression/11. Multiple Linear Regression in R.mp4
62.37 MB
7. Linear Regression/11. Multiple Linear Regression in R.srt
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7. Linear Regression/12. Test-train split.mp4
41.89 MB
7. Linear Regression/12. Test-train split.srt
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7. Linear Regression/13. Bias Variance trade-off.mp4
25.1 MB
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7. Linear Regression/14. Test train split in Python.mp4
44.89 MB
7. Linear Regression/14. Test train split in Python.srt
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7. Linear Regression/15. Test-Train Split in R.mp4
75.6 MB
7. Linear Regression/15. Test-Train Split in R.srt
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7. Linear Regression/16. Regression models other than OLS.mp4
16.55 MB
7. Linear Regression/16. Regression models other than OLS.srt
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7. Linear Regression/17. Subset selection techniques.mp4
79.06 MB
7. Linear Regression/17. Subset selection techniques.srt
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7. Linear Regression/18. Subset selection in R.mp4
63.54 MB
7. Linear Regression/18. Subset selection in R.srt
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7. Linear Regression/19. Shrinkage methods Ridge and Lasso.mp4
33.34 MB
7. Linear Regression/19. Shrinkage methods Ridge and Lasso.srt
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7. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.mp4
43.38 MB
7. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.srt
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7. Linear Regression/20. Ridge regression and Lasso in Python.mp4
128.84 MB
7. Linear Regression/20. Ridge regression and Lasso in Python.srt
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7. Linear Regression/21. Ridge regression and Lasso in R.mp4
103.43 MB
7. Linear Regression/21. Ridge regression and Lasso in R.srt
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7. Linear Regression/22. Heteroscedasticity.mp4
14.49 MB
7. Linear Regression/22. Heteroscedasticity.srt
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7. Linear Regression/3. Assessing accuracy of predicted coefficients.mp4
92.11 MB
7. Linear Regression/3. Assessing accuracy of predicted coefficients.srt
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7. Linear Regression/4. Assessing Model Accuracy RSE and R squared.mp4
43.59 MB
7. Linear Regression/4. Assessing Model Accuracy RSE and R squared.srt
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7. Linear Regression/5. Simple Linear Regression in Python.mp4
63.43 MB
7. Linear Regression/5. Simple Linear Regression in Python.srt
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7. Linear Regression/6. Simple Linear Regression in R.mp4
40.83 MB
7. Linear Regression/6. Simple Linear Regression in R.srt
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7. Linear Regression/7. Multiple Linear Regression.mp4
34.31 MB
7. Linear Regression/7. Multiple Linear Regression.srt
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7. Linear Regression/8. The F - statistic.mp4
55.98 MB
7. Linear Regression/8. The F - statistic.srt
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7. Linear Regression/9. Interpreting results of Categorical variables.mp4
22.51 MB
7. Linear Regression/9. Interpreting results of Categorical variables.srt
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8. Introduction to the classification Models/1. Three classification models and Data set.mp4
52.27 MB
8. Introduction to the classification Models/1. Three classification models and Data set.srt
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8. Introduction to the classification Models/1.1 Classification preprocessed data Python.csv
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8. Introduction to the classification Models/1.2 Classification preprocessed data R.csv
40.97 KB
8. Introduction to the classification Models/2. Importing the data into Python.mp4
6.86 MB
8. Introduction to the classification Models/2. Importing the data into Python.srt
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8. Introduction to the classification Models/2.1 Classification preprocessed data Python.csv
40.97 KB
8. Introduction to the classification Models/3. Importing the data into R.mp4
8.82 MB
8. Introduction to the classification Models/3. Importing the data into R.srt
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8. Introduction to the classification Models/3.1 Classification preprocessed data R.csv
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8. Introduction to the classification Models/4. The problem statements.mp4
17.08 MB
8. Introduction to the classification Models/4. The problem statements.srt
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8. Introduction to the classification Models/5. Why can't we use Linear Regression.mp4
16.94 MB
8. Introduction to the classification Models/5. Why can't we use Linear Regression.srt
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9. Logistic Regression/1. Logistic Regression.mp4
32.92 MB
9. Logistic Regression/1. Logistic Regression.srt
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9. Logistic Regression/10. Evaluating performance of model.mp4
35.16 MB
9. Logistic Regression/10. Evaluating performance of model.srt
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9. Logistic Regression/11. Evaluating model performance in Python.mp4
9.01 MB
9. Logistic Regression/11. Evaluating model performance in Python.srt
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9. Logistic Regression/12. Predicting probabilities, assigning classes and making Confusion Matrix in R.mp4
55.7 MB
9. Logistic Regression/12. Predicting probabilities, assigning classes and making Confusion Matrix in R.srt
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9. Logistic Regression/2. Training a Simple Logistic Model in Python.mp4
47.87 MB
9. Logistic Regression/2. Training a Simple Logistic Model in Python.srt
10.76 KB
9. Logistic Regression/3. Training a Simple Logistic model in R.mp4
25.57 MB
9. Logistic Regression/3. Training a Simple Logistic model in R.srt
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9. Logistic Regression/4. Result of Simple Logistic Regression.mp4
26.93 MB
9. Logistic Regression/4. Result of Simple Logistic Regression.srt
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9. Logistic Regression/5. Logistic with multiple predictors.mp4
8.54 MB
9. Logistic Regression/5. Logistic with multiple predictors.srt
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9. Logistic Regression/6. Training multiple predictor Logistic model in Python.mp4
26.25 MB
9. Logistic Regression/6. Training multiple predictor Logistic model in Python.srt
6.25 KB
9. Logistic Regression/7. Training multiple predictor Logistic model in R.mp4
15.78 MB
9. Logistic Regression/7. Training multiple predictor Logistic model in R.srt
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9. Logistic Regression/8. Confusion Matrix.mp4
21.1 MB
9. Logistic Regression/8. Confusion Matrix.srt
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9. Logistic Regression/9. Creating Confusion Matrix in Python.mp4
51.25 MB
9. Logistic Regression/9. Creating Confusion Matrix in Python.srt
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