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| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 1. Basic Terminologies.mp4 |
40.44MB |
| 1. Basic Terminologies.srt |
9.52KB |
| 1. Building,Compiling and Training.mp4 |
130.73MB |
| 1. Building,Compiling and Training.srt |
15.42KB |
| 1. Building Neural Network for Regression Problem.mp4 |
155.86MB |
| 1. Building Neural Network for Regression Problem.srt |
21.71KB |
| 1. Building Regression Model with Functional AP.mp4 |
131.14MB |
| 1. Building Regression Model with Functional AP.srt |
13.07KB |
| 1. Congratulations & About your certificate.html |
1.60KB |
| 1. Different ways to create ANN using Keras.mp4 |
10.81MB |
| 1. Different ways to create ANN using Keras.srt |
1.87KB |
| 1. Gathering Business Knowledge.mp4 |
22.29MB |
| 1. Gathering Business Knowledge.srt |
3.90KB |
| 1. Hyperparameters.mp4 |
45.36MB |
| 1. Hyperparameters.srt |
8.95KB |
| 1. Hyperparameter Tuning.mp4 |
60.64MB |
| 1. Hyperparameter Tuning.mp4 |
60.63MB |
| 1. Hyperparameter Tuning.srt |
9.43KB |
| 1. Hyperparameter Tuning.srt |
9.43KB |
| 1. Installing Python and Anaconda.mp4 |
16.28MB |
| 1. Installing Python and Anaconda.srt |
2.58KB |
| 1. Installing R and R studio.mp4 |
35.70MB |
| 1. Installing R and R studio.srt |
5.63KB |
| 1. Introduction.mp4 |
29.10MB |
| 1. Introduction.srt |
4.60KB |
| 1. Keras and Tensorflow.mp4 |
14.92MB |
| 1. Keras and Tensorflow.srt |
3.56KB |
| 1. Perceptron.mp4 |
44.76MB |
| 1. Perceptron.srt |
9.69KB |
| 1. Python - Dataset for classification problem.mp4 |
56.18MB |
| 1. Python - Dataset for classification problem.srt |
7.16KB |
| 1. Saving - Restoring Models and Using Callbacks.mp4 |
216.10MB |
| 1. Saving - Restoring Models and Using Callbacks.mp4 |
151.63MB |
| 1. Saving - Restoring Models and Using Callbacks.srt |
18.79KB |
| 1. Saving - Restoring Models and Using Callbacks.srt |
20.36KB |
| 1. Some Important Concepts.mp4 |
62.18MB |
| 1. Some Important Concepts.srt |
13.10KB |
| 1. Test-train split.mp4 |
41.88MB |
| 1. Test-train split.srt |
10.05KB |
| 10. Outlier Treatment in Python.mp4 |
70.25MB |
| 10. Outlier Treatment in Python.srt |
13.00KB |
| 11. Outlier Treatment in R.mp4 |
30.75MB |
| 11. Outlier Treatment in R.srt |
4.28KB |
| 12. Missing Value imputation.mp4 |
24.99MB |
| 12. Missing Value imputation.srt |
4.08KB |
| 13. Missing Value Imputation in Python.mp4 |
23.42MB |
| 13. Missing Value Imputation in Python.srt |
4.06KB |
| 14. Missing Value imputation in R.mp4 |
25.99MB |
| 14. Missing Value imputation in R.srt |
3.46KB |
| 15. Seasonality in Data.mp4 |
17.04MB |
| 15. Seasonality in Data.srt |
3.78KB |
| 16. Bi-variate Analysis and Variable Transformation.mp4 |
100.47MB |
| 16. Bi-variate Analysis and Variable Transformation.srt |
18.29KB |
| 17. Variable transformation and deletion in Python.mp4 |
44.12MB |
| 17. Variable transformation and deletion in Python.srt |
7.54KB |
| 18. Variable transformation in R.mp4 |
55.42MB |
| 18. Variable transformation in R.srt |
9.04KB |
| 19. Non Usable Variables.mp4 |
20.25MB |
| 19. Non Usable Variables.srt |
5.39KB |
| 2. Activation Functions.mp4 |
34.63MB |
| 2. Activation Functions.srt |
7.85KB |
| 2. Basics of R and R studio.mp4 |
38.85MB |
| 2. Basics of R and R studio.srt |
10.83KB |
| 2. Bias Variance trade-off.mp4 |
25.10MB |
| 2. Bias Variance trade-off.srt |
6.37KB |
| 2. Building the Neural Network using Keras.mp4 |
79.14MB |
| 2. Building the Neural Network using Keras.srt |
11.96KB |
| 2. Complex Architectures using Functional API.mp4 |
79.58MB |
| 2. Complex Architectures using Functional API.srt |
8.28KB |
| 2. Course Resources.html |
327B |
| 2. Data Exploration.mp4 |
20.52MB |
| 2. Data Exploration.srt |
3.60KB |
| 2. Evaluating and Predicting.mp4 |
99.26MB |
| 2. Evaluating and Predicting.srt |
9.43KB |
| 2. Gradient Descent.mp4 |
60.33MB |
| 2. Gradient Descent.srt |
11.93KB |
| 2. Installing Tensorflow and Keras in Python.mp4 |
20.07MB |
| 2. Installing Tensorflow and Keras in Python.srt |
3.79KB |
| 2. Opening Jupyter Notebook.mp4 |
65.20MB |
| 2. Opening Jupyter Notebook.srt |
9.14KB |
| 2. Python - Normalization and Test-Train split.mp4 |
44.21MB |
| 2. Python - Normalization and Test-Train split.srt |
5.73KB |
| 2. Quiz.html |
166B |
| 2. Quiz.html |
166B |
| 2. Using Functional API for complex architectures.mp4 |
92.14MB |
| 2. Using Functional API for complex architectures.srt |
11.50KB |
| 20. Dummy variable creation Handling qualitative data.mp4 |
36.84MB |
| 20. Dummy variable creation Handling qualitative data.srt |
4.86KB |
| 21. Dummy variable creation in Python.mp4 |
26.54MB |
| 21. Dummy variable creation in Python.srt |
5.51KB |
| 22. Dummy variable creation in R.mp4 |
43.98MB |
| 22. Dummy variable creation in R.srt |
5.19KB |
| 3.1 House_Price.csv |
53.49KB |
| 3. Back Propagation.mp4 |
122.20MB |
| 3. Back Propagation.srt |
22.78KB |
| 3. Compiling and Training the Neural Network model.mp4 |
81.65MB |
| 3. Compiling and Training the Neural Network model.srt |
9.59KB |
| 3. Installing TensorFlow and Keras in R.mp4 |
22.83MB |
| 3. Installing TensorFlow and Keras in R.srt |
2.98KB |
| 3. Introduction to Jupyter.mp4 |
40.92MB |
| 3. Introduction to Jupyter.srt |
12.31KB |
| 3. Packages in R.mp4 |
82.96MB |
| 3. Packages in R.srt |
11.46KB |
| 3. Python - Creating Perceptron model.mp4 |
86.59MB |
| 3. Python - Creating Perceptron model.srt |
14.53KB |
| 3. R - Dataset, Normalization and Test-Train set.mp4 |
111.80MB |
| 3. R - Dataset, Normalization and Test-Train set.srt |
12.07KB |
| 3. Test train split in Python.mp4 |
44.86MB |
| 3. Test train split in Python.srt |
8.05KB |
| 3. The Data and the Data Dictionary.mp4 |
69.34MB |
| 3. The Data and the Data Dictionary.srt |
7.82KB |
| 4. Arithmetic operators in Python Python Basics.mp4 |
12.75MB |
| 4. Arithmetic operators in Python Python Basics.srt |
3.99KB |
| 4. Evaluating performance and Predicting using Keras.mp4 |
69.87MB |
| 4. Evaluating performance and Predicting using Keras.srt |
9.02KB |
| 4. Importing Data in Python.mp4 |
27.84MB |
| 4. Importing Data in Python.srt |
5.58KB |
| 4. Inputting data part 1 Inbuilt datasets of R.mp4 |
40.73MB |
| 4. Inputting data part 1 Inbuilt datasets of R.srt |
4.04KB |
| 4. Test train split in R.mp4 |
75.61MB |
| 4. Test train split in R.srt |
8.37KB |
| 5. Importing the dataset into R.mp4 |
13.11MB |
| 5. Importing the dataset into R.srt |
2.60KB |
| 5. Inputting data part 2 Manual data entry.mp4 |
25.52MB |
| 5. Inputting data part 2 Manual data entry.srt |
2.96KB |
| 5. Strings in Python Python Basics.mp4 |
64.44MB |
| 5. Strings in Python Python Basics.srt |
16.43KB |
| 6. Inputting data part 3 Importing from CSV or Text files.mp4 |
60.06MB |
| 6. Inputting data part 3 Importing from CSV or Text files.srt |
6.39KB |
| 6. Lists, Tuples and Directories Python Basics.mp4 |
60.32MB |
| 6. Lists, Tuples and Directories Python Basics.srt |
17.01KB |
| 6. Univariate Analysis and EDD.mp4 |
24.21MB |
| 6. Univariate Analysis and EDD.srt |
3.44KB |
| 7. Creating Barplots in R.mp4 |
96.76MB |
| 7. Creating Barplots in R.srt |
13.42KB |
| 7. EDD in Python.mp4 |
61.79MB |
| 7. EDD in Python.srt |
10.36KB |
| 7. Working with Numpy Library of Python.mp4 |
43.89MB |
| 7. Working with Numpy Library of Python.srt |
10.47KB |
| 8.1 Product.txt |
139.48KB |
| 8.2 Customer.csv |
64.02KB |
| 8. Creating Histograms in R.mp4 |
42.01MB |
| 8. Creating Histograms in R.srt |
5.90KB |
| 8. EDD in R.mp4 |
96.98MB |
| 8. EDD in R.srt |
11.55KB |
| 8. Working with Pandas Library of Python.mp4 |
46.90MB |
| 8. Working with Pandas Library of Python.srt |
8.15KB |
| 9. Outlier Treatment.mp4 |
24.49MB |
| 9. Outlier Treatment.srt |
4.46KB |
| 9. Working with Seaborn Library of Python.mp4 |
40.36MB |
| 9. Working with Seaborn Library of Python.srt |
7.53KB |
| TutsNode.com.txt |
63B |