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Category:
Language:
English
Total Size:
3.0 GB
Info Hash:
023489E261F71D8D732DF009E55D6FF2895BF056
Added By:
Added:
Oct. 28, 2023, 6:17 a.m.
Stats:
|
(Last updated: May 11, 2025, 1:28 a.m.)
| File | Size |
|---|---|
| 1. Welcome to the course.mp4 | 21.4 MB |
| 1. Welcome to the course.srt | 3.1 KB |
| 2. Introduction to Neural Networks and Course flow.mp4 | 29.1 MB |
| 2. Introduction to Neural Networks and Course flow.srt | 4.6 KB |
| 3. Course resources.html | 117 bytes |
| 3.1 Files_ANN_Py.zip | 10.5 MB |
| 1. Different ways to create ANN using Keras.mp4 | 10.8 MB |
| 1. Different ways to create ANN using Keras.srt | 1.9 KB |
| 2. Building the Neural Network using Keras.mp4 | 79.1 MB |
| 2. Building the Neural Network using Keras.srt | 12.0 KB |
| 3. Compiling and Training the Neural Network model.mp4 | 81.7 MB |
| 3. Compiling and Training the Neural Network model.srt | 9.6 KB |
| 4. Evaluating performance and Predicting using Keras.mp4 | 69.9 MB |
| 4. Evaluating performance and Predicting using Keras.srt | 9.0 KB |
| 1. Building Neural Network for Regression Problem.mp4 | 155.9 MB |
| 1. Building Neural Network for Regression Problem.srt | 21.7 KB |
| 1. Using Functional API for complex architectures.mp4 | 92.1 MB |
| 1. Using Functional API for complex architectures.srt | 11.5 KB |
| 1. Saving - Restoring Models and Using Callbacks.mp4 | 151.6 MB |
| 1. Saving - Restoring Models and Using Callbacks.srt | 18.8 KB |
| 1. Hyperparameter Tuning.mp4 | 60.6 MB |
| 1. Hyperparameter Tuning.srt | 9.4 KB |
| 1. Gathering Business Knowledge.mp4 | 22.3 MB |
| 1. Gathering Business Knowledge.srt | 3.9 KB |
| 10. Missing Value Imputation in Python.mp4 | 23.4 MB |
| 10. Missing Value Imputation in Python.srt | 4.1 KB |
| 11. Seasonality in Data.mp4 | 17.0 MB |
| 11. Seasonality in Data.srt | 3.8 KB |
| 12. Bi-variate analysis and Variable transformation.mp4 | 100.4 MB |
| 12. Bi-variate analysis and Variable transformation.srt | 18.3 KB |
| 13. Variable transformation and deletion in Python.mp4 | 44.1 MB |
| 13. Variable transformation and deletion in Python.srt | 7.5 KB |
| 14. Non-usable variables.mp4 | 20.2 MB |
| 14. Non-usable variables.srt | 5.4 KB |
| 15. Dummy variable creation Handling qualitative data.mp4 | 36.8 MB |
| 15. Dummy variable creation Handling qualitative data.srt | 4.9 KB |
| 16. Dummy variable creation in Python.mp4 | 26.5 MB |
| 16. Dummy variable creation in Python.srt | 5.5 KB |
| 17. Correlation Analysis.mp4 | 71.6 MB |
| 17. Correlation Analysis.srt | 11.0 KB |
| 18. Correlation Analysis in Python.mp4 | 55.3 MB |
| 18. Correlation Analysis in Python.srt | 6.6 KB |
| 2. Data Exploration.mp4 | 20.5 MB |
| 2. Data Exploration.srt | 3.6 KB |
| 3. The Dataset and the Data Dictionary.mp4 | 69.4 MB |
| 3. The Dataset and the Data Dictionary.srt | 7.8 KB |
| 4. Importing Data in Python.mp4 | 27.8 MB |
| 4. Importing Data in Python.srt | 5.6 KB |
| 5. Univariate analysis and EDD.mp4 | 24.2 MB |
| 5. Univariate analysis and EDD.srt | 3.4 KB |
| 6. EDD in Python.mp4 | 61.8 MB |
| 6. EDD in Python.srt | 10.4 KB |
| 7. Outlier Treatment.mp4 | 24.5 MB |
| 7. Outlier Treatment.srt | 4.5 KB |
| 8. Outlier Treatment in Python.mp4 | 70.2 MB |
| 8. Outlier Treatment in Python.srt | 13.0 KB |
| 9. Missing Value Imputation.mp4 | 25.0 MB |
| 9. Missing Value Imputation.srt | 4.1 KB |
| 1. The Problem Statement.mp4 | 9.4 MB |
| 1. The Problem Statement.srt | 1.6 KB |
| 10. Test-train split.mp4 | 41.9 MB |
| 10. Test-train split.srt | 10.1 KB |
| 11. Bias Variance trade-off.mp4 | 25.1 MB |
| 11. Bias Variance trade-off.srt | 6.4 KB |
| 12. Test train split in Python.mp4 | 44.9 MB |
| 12. Test train split in Python.srt | 8.1 KB |
| 2. Basic Equations and Ordinary Least Squares (OLS) method.mp4 | 43.4 MB |
| 2. Basic Equations and Ordinary Least Squares (OLS) method.srt | 9.9 KB |
| 3. Assessing accuracy of predicted coefficients.mp4 | 92.1 MB |
| 3. Assessing accuracy of predicted coefficients.srt | 15.9 KB |
| 4. Assessing Model Accuracy RSE and R squared.mp4 | 43.6 MB |
| 4. Assessing Model Accuracy RSE and R squared.srt | 8.0 KB |
| 5. Simple Linear Regression in Python.mp4 | 63.4 MB |
| 5. Simple Linear Regression in Python.srt | 11.4 KB |
| 6. Multiple Linear Regression.mp4 | 34.3 MB |
| 6. Multiple Linear Regression.srt | 5.7 KB |
| 7. The F - statistic.mp4 | 56.0 MB |
| 7. The F - statistic.srt | 9.0 KB |
| 8. Interpreting results of Categorical variables.mp4 | 22.5 MB |
| 8. Interpreting results of Categorical variables.srt | 5.3 KB |
| 9. Multiple Linear Regression in Python.mp4 | 69.7 MB |
| 9. Multiple Linear Regression in Python.srt | 12.3 KB |
| 1. Neural Networks Classification Assignment.html | 173 bytes |
| 1. Installing Python and Anaconda.mp4 | 16.3 MB |
| 1. Installing Python and Anaconda.srt | 2.6 KB |
| 2. Opening Jupyter Notebook.mp4 | 65.2 MB |
| 2. Opening Jupyter Notebook.srt | 9.1 KB |
| 3. Introduction to Jupyter.mp4 | 40.9 MB |
| 3. Introduction to Jupyter.srt | 12.3 KB |
| 4. Arithmetic operators in Python Python Basics.mp4 | 12.7 MB |
| 4. Arithmetic operators in Python Python Basics.srt | 4.0 KB |
| 5. Strings in Python Python Basics.mp4 | 64.4 MB |
| 5. Strings in Python Python Basics.srt | 16.4 KB |
| 6. Lists, Tuples and Directories Python Basics.mp4 | 60.3 MB |
| 6. Lists, Tuples and Directories Python Basics.srt | 17.0 KB |
| 7. Working with Numpy Library of Python.mp4 | 43.9 MB |
| 7. Working with Numpy Library of Python.srt | 10.5 KB |
| 8. Working with Pandas Library of Python.mp4 | 46.9 MB |
| 8. Working with Pandas Library of Python.srt | 8.2 KB |
| 9. Working with Seaborn Library of Python.mp4 | 40.4 MB |
| 9. Working with Seaborn Library of Python.srt | 7.5 KB |
| 1. Perceptron.mp4 | 44.8 MB |
| 1. Perceptron.srt | 9.7 KB |
| 2. Activation Functions.mp4 | 34.6 MB |
| 2. Activation Functions.srt | 7.9 KB |
| 3. Python - Creating Perceptron model.mp4 | 86.6 MB |
| 3. Python - Creating Perceptron model.srt | 14.5 KB |
| 1. Basic Terminologies.mp4 | 40.4 MB |
| 1. Basic Terminologies.srt | 9.5 KB |
| 2. Gradient Descent.mp4 | 60.3 MB |
| 2. Gradient Descent.srt | 11.9 KB |
| 3. Back Propagation.mp4 | 122.2 MB |
| 3. Back Propagation.srt | 22.8 KB |
| 1. Some Important Concepts.mp4 | 62.2 MB |
| 1. Some Important Concepts.srt | 13.1 KB |
| 2. Quiz.html | 169 bytes |
| 1. Hyperparameters.mp4 | 45.3 MB |
| 1. Hyperparameters.srt | 8.9 KB |
| 1. Test your conceptual understanding.html | 169 bytes |
| 1. Keras and Tensorflow.mp4 | 14.9 MB |
| 1. Keras and Tensorflow.srt | 3.6 KB |
| 2. Installing Tensorflow and Keras.mp4 | 20.1 MB |
| 2. Installing Tensorflow and Keras.srt | 3.8 KB |
| 1. Dataset for classification.mp4 | 56.1 MB |
| 1. Dataset for classification.srt | 7.2 KB |
| 2. Normalization and Test-Train split.mp4 | 44.2 MB |
| 2. Normalization and Test-Train split.srt | 5.7 KB |
| Readme.txt | 962 bytes |
| [GigaCourse.com].url | 49 bytes |
Name
DL
Uploader
Size
S/L
Added
-
693.5 MB
[0
/
10]
2023-10-24
| Uploaded by freecoursewb | Size 693.5 MB | Health [ 0 /10 ] | Added 2023-10-24 |
-
807.1 MB
[0
/
8]
2023-10-24
| Uploaded by freecoursewb | Size 807.1 MB | Health [ 0 /8 ] | Added 2023-10-24 |
NOTE
SOURCE: Udemy Neural Networks ANN using Keras and TensorFlow in Python
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