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Learned the basic Neural Network model creation.
The steps involve:
1. Importing libraries
2. Importing the dataset
3. Preprocessing (outliers, encoding variables, missing values)
4. Selecting the features X and Y Target
5. Train test Split the dataset
6. Standardize the data (if necessary)
7. Building the model (input layers, and output layers)
8. Compile the model
9. Training the model
10. Evaluating the model
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1. Epochs: Number of Iterations
2. Verbose: Number of Output or format (value=1 is often used)
3. Training loss and Training Accuracy: obtained while training the model (often high)
4. Testing loss and Testing Accuracy: obtained while testing/evaluating the model (often a bit low)
5. With an increasing number of epochs: the loss will decrease and the accuracy will increase.
6. Call back function: Select the best epoch number and stop the further execution.
Done
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our first neural network creation in python
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I have done this video.
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I learned in this lecture with 100% practice.
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I have done this lecture with 100% practice.
This very informative video covers all the steps for model building, from data upload to the construction of building models with input, and output layers, and how to set optimizers, loss, and accuracy. Model training and evalution
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AOA, I learned in this lecture how to build a simple neural network model in Python using the Tensor Flow library, and I completed this lecture with 100% practice.
ALLAH PAK aap ko sahat o aafiyat wali lambi umar ata kray aor ap ko dono jahan ki bhalian naseeb farmaey aur aap ke walid-e-mohtram ko karwat karwat jannat ata farmaye,Ameen.
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