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@@ -253,16 +253,6 @@ Get started with the genetic algorithm by reading the tutorial titled [**Introdu
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[](https://www.linkedin.com/pulse/introduction-optimization-genetic-algorithm-ahmed-gad)
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## Tutorial: Build Neural Networks in Python
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Read about building neural networks in Python through the tutorial titled [**Artificial Neural Network Implementation using NumPy and Classification of the Fruits360 Image Dataset**](https://www.linkedin.com/pulse/artificial-neural-network-implementation-using-numpy-fruits360-gad) available at these links:
*[Towards Data Science](https://towardsdatascience.com/artificial-neural-network-implementation-using-numpy-and-classification-of-the-fruits360-image-3c56affa4491)
## Tutorial: Optimize Neural Networks with Genetic Algorithm
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Read about training neural networks using the genetic algorithm through the tutorial titled [**Artificial Neural Networks Optimization using Genetic Algorithm with Python**](https://www.linkedin.com/pulse/artificial-neural-networks-optimization-using-genetic-ahmed-gad) available at these links:
@@ -273,29 +263,6 @@ Read about training neural networks using the genetic algorithm through the tuto
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[](https://www.linkedin.com/pulse/artificial-neural-networks-optimization-using-genetic-ahmed-gad)
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## Tutorial: Building CNN in Python
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To start with coding the genetic algorithm, you can check the tutorial titled [**Building Convolutional Neural Network using NumPy from Scratch**](https://www.linkedin.com/pulse/building-convolutional-neural-network-using-numpy-from-ahmed-gad) available at these links:
[This tutorial](https://www.linkedin.com/pulse/building-convolutional-neural-network-using-numpy-from-ahmed-gad)) is prepared based on a previous version of the project but it still a good resource to start with coding CNNs.
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[](https://www.linkedin.com/pulse/building-convolutional-neural-network-using-numpy-from-ahmed-gad)
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## Tutorial: Derivation of CNN from FCNN
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Get started with the genetic algorithm by reading the tutorial titled [**Derivation of Convolutional Neural Network from Fully Connected Network Step-By-Step**](https://www.linkedin.com/pulse/derivation-convolutional-neural-network-from-fully-connected-gad) which is available at these links:
*[Towards Data Science](https://towardsdatascience.com/derivation-of-convolutional-neural-network-from-fully-connected-network-step-by-step-b42ebafa5275)
[](https://www.linkedin.com/pulse/derivation-convolutional-neural-network-from-fully-connected-gad)
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## Book: Practical Computer Vision Applications Using Deep Learning with CNNs
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You can also check my book cited as [**Ahmed Fawzy Gad 'Practical Computer Vision Applications Using Deep Learning with CNNs'. Dec. 2018, Apress, 978-1-4842-4167-7**](https://www.amazon.com/Practical-Computer-Vision-Applications-Learning/dp/1484241665) which discusses neural networks, convolutional neural networks, deep learning, genetic algorithm, and more.
raiseException("The output from the gene_constraint callable/function must be a list or NumPy array that is subset of the passed values (second argument).")
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# After going through all the values, check if any value satisfies the constraint.
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iflen(filtered_values_indices) >0:
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iflen(filtered_values) >0:
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# At least one value was found that meets the gene constraint.
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pass
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else:
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# No value found for the current gene that satisfies the constraint.
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ifnotself.suppress_warnings:
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warnings.warn(f"No value found for the gene at index {gene_idx} with value {solution[gene_idx]} that satisfies its gene constraint.")
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ifnotself.suppress_warnings: warnings.warn(f"Failed to find a value that satisfies its gene constraint for the gene at index {gene_idx} with value {solution[gene_idx]} at generation {self.generations_completed}.")
ifnotself.suppress_warnings: warnings.warn(f"Failed to find a unique value for gene with index {duplicate_index} whose value is {solution[duplicate_index]}. Consider adding more values in the gene space or use a wider range for initial population or random mutation.")
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ifnotself.suppress_warnings: warnings.warn(f"Failed to find a unique value for gene with index {duplicate_index} whose value is {solution[duplicate_index]} at generation {self.generations_completed}. Consider adding more values in the gene space or use a wider range for initial population or random mutation.")
ifnotself.suppress_warnings: warnings.warn(f"Failed to find a unique value for gene with index {duplicate_index} whose value is {solution[duplicate_index]}. Consider adding more values in the gene space or use a wider range for initial population or random mutation.")
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ifnotself.suppress_warnings: warnings.warn(f"Failed to find a unique value for gene with index {duplicate_index} whose value is {solution[duplicate_index]} at generation {self.generations_completed+1}. Consider adding more values in the gene space or use a wider range for initial population or random mutation.")
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