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[GigaCourse.com] Udemy - Neural Networks (ANN) using Keras and TensorFlow in Python

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File Name
Size
1. Introduction/1. Welcome to the course.mp4
21 MB
1. Introduction/1. Welcome to the course.srt
3.1 kB
1. Introduction/2. Introduction to Neural Networks and Course flow.mp4
29 MB
1. Introduction/2. Introduction to Neural Networks and Course flow.srt
4.6 kB
1. Introduction/3. Course resources.html
117 B
1. Introduction/3.1 Files_ANN_Py.zip
10 MB
10. Python - Building and training the Model/1. Different ways to create ANN using Keras.mp4
11 MB
10. Python - Building and training the Model/1. Different ways to create ANN using Keras.srt
1.9 kB
10. Python - Building and training the Model/2. Building the Neural Network using Keras.mp4
79 MB
10. Python - Building and training the Model/2. Building the Neural Network using Keras.srt
12 kB
10. Python - Building and training the Model/3. Compiling and Training the Neural Network model.mp4
82 MB
10. Python - Building and training the Model/3. Compiling and Training the Neural Network model.srt
9.6 kB
10. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.mp4
70 MB
10. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.srt
9.0 kB
11. Python - Solving a Regression problem using ANN/1. Building Neural Network for Regression Problem.mp4
156 MB
11. Python - Solving a Regression problem using ANN/1. Building Neural Network for Regression Problem.srt
22 kB
12. Complex ANN Architectures using Functional API/1. Using Functional API for complex architectures.mp4
92 MB
12. Complex ANN Architectures using Functional API/1. Using Functional API for complex architectures.srt
12 kB
13. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4
152 MB
13. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.srt
19 kB
14. Hyperparameter Tuning/1. Hyperparameter Tuning.mp4
61 MB
14. Hyperparameter Tuning/1. Hyperparameter Tuning.srt
9.4 kB
15. Add-on 1 Data Preprocessing/1. Gathering Business Knowledge.mp4
22 MB
15. Add-on 1 Data Preprocessing/1. Gathering Business Knowledge.srt
3.9 kB
15. Add-on 1 Data Preprocessing/10. Missing Value Imputation in Python.mp4
23 MB
15. Add-on 1 Data Preprocessing/10. Missing Value Imputation in Python.srt
4.1 kB
15. Add-on 1 Data Preprocessing/11. Seasonality in Data.mp4
17 MB
15. Add-on 1 Data Preprocessing/11. Seasonality in Data.srt
3.8 kB
15. Add-on 1 Data Preprocessing/12. Bi-variate analysis and Variable transformation.mp4
100 MB
15. Add-on 1 Data Preprocessing/12. Bi-variate analysis and Variable transformation.srt
18 kB
15. Add-on 1 Data Preprocessing/13. Variable transformation and deletion in Python.mp4
44 MB
15. Add-on 1 Data Preprocessing/13. Variable transformation and deletion in Python.srt
7.5 kB
15. Add-on 1 Data Preprocessing/14. Non-usable variables.mp4
20 MB
15. Add-on 1 Data Preprocessing/14. Non-usable variables.srt
5.4 kB
15. Add-on 1 Data Preprocessing/15. Dummy variable creation Handling qualitative data.mp4
37 MB
15. Add-on 1 Data Preprocessing/15. Dummy variable creation Handling qualitative data.srt
4.9 kB
15. Add-on 1 Data Preprocessing/16. Dummy variable creation in Python.mp4
26 MB
15. Add-on 1 Data Preprocessing/16. Dummy variable creation in Python.srt
5.5 kB
15. Add-on 1 Data Preprocessing/17. Correlation Analysis.mp4
72 MB
15. Add-on 1 Data Preprocessing/17. Correlation Analysis.srt
11 kB
15. Add-on 1 Data Preprocessing/18. Correlation Analysis in Python.mp4
55 MB
15. Add-on 1 Data Preprocessing/18. Correlation Analysis in Python.srt
6.6 kB
15. Add-on 1 Data Preprocessing/2. Data Exploration.mp4
20 MB
15. Add-on 1 Data Preprocessing/2. Data Exploration.srt
3.6 kB
15. Add-on 1 Data Preprocessing/3. The Dataset and the Data Dictionary.mp4
69 MB
15. Add-on 1 Data Preprocessing/3. The Dataset and the Data Dictionary.srt
7.8 kB
15. Add-on 1 Data Preprocessing/4. Importing Data in Python.mp4
28 MB
15. Add-on 1 Data Preprocessing/4. Importing Data in Python.srt
5.6 kB
15. Add-on 1 Data Preprocessing/5. Univariate analysis and EDD.mp4
24 MB
15. Add-on 1 Data Preprocessing/5. Univariate analysis and EDD.srt
3.4 kB
15. Add-on 1 Data Preprocessing/6. EDD in Python.mp4
62 MB
15. Add-on 1 Data Preprocessing/6. EDD in Python.srt
10 kB
15. Add-on 1 Data Preprocessing/7. Outlier Treatment.mp4
24 MB
15. Add-on 1 Data Preprocessing/7. Outlier Treatment.srt
4.5 kB
15. Add-on 1 Data Preprocessing/8. Outlier Treatment in Python.mp4
70 MB
15. Add-on 1 Data Preprocessing/8. Outlier Treatment in Python.srt
13 kB
15. Add-on 1 Data Preprocessing/9. Missing Value Imputation.mp4
25 MB
15. Add-on 1 Data Preprocessing/9. Missing Value Imputation.srt
4.1 kB
16. Add-on 2 Classic ML models - Linear Regression/1. The Problem Statement.mp4
9.4 MB
16. Add-on 2 Classic ML models - Linear Regression/1. The Problem Statement.srt
1.6 kB
16. Add-on 2 Classic ML models - Linear Regression/10. Test-train split.mp4
42 MB
16. Add-on 2 Classic ML models - Linear Regression/10. Test-train split.srt
10 kB
16. Add-on 2 Classic ML models - Linear Regression/11. Bias Variance trade-off.mp4
25 MB
16. Add-on 2 Classic ML models - Linear Regression/11. Bias Variance trade-off.srt
6.4 kB
16. Add-on 2 Classic ML models - Linear Regression/12. Test train split in Python.mp4
45 MB
16. Add-on 2 Classic ML models - Linear Regression/12. Test train split in Python.srt
8.1 kB
16. Add-on 2 Classic ML models - Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.mp4
43 MB
16. Add-on 2 Classic ML models - Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.srt
9.9 kB
16. Add-on 2 Classic ML models - Linear Regression/3. Assessing accuracy of predicted coefficients.mp4
92 MB
16. Add-on 2 Classic ML models - Linear Regression/3. Assessing accuracy of predicted coefficients.srt
16 kB
16. Add-on 2 Classic ML models - Linear Regression/4. Assessing Model Accuracy RSE and R squared.mp4
44 MB
16. Add-on 2 Classic ML models - Linear Regression/4. Assessing Model Accuracy RSE and R squared.srt
8.0 kB
16. Add-on 2 Classic ML models - Linear Regression/5. Simple Linear Regression in Python.mp4
63 MB
16. Add-on 2 Classic ML models - Linear Regression/5. Simple Linear Regression in Python.srt
11 kB
16. Add-on 2 Classic ML models - Linear Regression/6. Multiple Linear Regression.mp4
34 MB
16. Add-on 2 Classic ML models - Linear Regression/6. Multiple Linear Regression.srt
5.7 kB
16. Add-on 2 Classic ML models - Linear Regression/7. The F - statistic.mp4
56 MB
16. Add-on 2 Classic ML models - Linear Regression/7. The F - statistic.srt
9.0 kB
16. Add-on 2 Classic ML models - Linear Regression/8. Interpreting results of Categorical variables.mp4
22 MB
16. Add-on 2 Classic ML models - Linear Regression/8. Interpreting results of Categorical variables.srt
5.3 kB
16. Add-on 2 Classic ML models - Linear Regression/9. Multiple Linear Regression in Python.mp4
70 MB
16. Add-on 2 Classic ML models - Linear Regression/9. Multiple Linear Regression in Python.srt
12 kB
17. Practice Assignment/1. Neural Networks Classification Assignment.html
173 B
2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp4
16 MB
2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.srt
2.6 kB
2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4
65 MB
2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.srt
9.1 kB
2. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.mp4
41 MB
2. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.srt
12 kB
2. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.mp4
13 MB
2. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.srt
4.0 kB
2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4
64 MB
2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.srt
16 kB
2. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp4
60 MB
2. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.srt
17 kB
2. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.mp4
44 MB
2. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.srt
10 kB
2. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.mp4
47 MB
2. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.srt
8.2 kB
2. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.mp4
40 MB
2. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.srt
7.5 kB
3. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.mp4
45 MB
3. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.srt
9.7 kB
3. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.mp4
35 MB
3. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.srt
7.9 kB
3. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.mp4
87 MB
3. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.srt
14 kB
4. Neural Networks - Stacking cells to create network/1. Basic Terminologies.mp4
40 MB
4. Neural Networks - Stacking cells to create network/1. Basic Terminologies.srt
9.5 kB
4. Neural Networks - Stacking cells to create network/2. Gradient Descent.mp4
60 MB
4. Neural Networks - Stacking cells to create network/2. Gradient Descent.srt
12 kB
4. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4
122 MB
4. Neural Networks - Stacking cells to create network/3. Back Propagation.srt
23 kB
5. Important concepts Common Interview questions/1. Some Important Concepts.mp4
62 MB
5. Important concepts Common Interview questions/1. Some Important Concepts.srt
13 kB
5. Important concepts Common Interview questions/2. Quiz.html
169 B
6. Standard Model Parameters/1. Hyperparameters.mp4
45 MB
6. Standard Model Parameters/1. Hyperparameters.srt
8.9 kB
7. Practice Test/1. Test your conceptual understanding.html
169 B
8. Tensorflow and Keras/1. Keras and Tensorflow.mp4
15 MB
8. Tensorflow and Keras/1. Keras and Tensorflow.srt
3.6 kB
8. Tensorflow and Keras/2. Installing Tensorflow and Keras.mp4
20 MB
8. Tensorflow and Keras/2. Installing Tensorflow and Keras.srt
3.8 kB
9. Python - Dataset for classification problem/1. Dataset for classification.mp4
56 MB
9. Python - Dataset for classification problem/1. Dataset for classification.srt
7.2 kB
9. Python - Dataset for classification problem/2. Normalization and Test-Train split.mp4
44 MB
9. Python - Dataset for classification problem/2. Normalization and Test-Train split.srt
5.7 kB
Readme.txt
962 B
[GigaCourse.com].url
49 B