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What did you observe?
              This creates a mix of effects on the image. The positive and negative values in the kernel work together to
              produce a more complex transformation. You might notice sharpening, edge detection, or contrast changes in
              the image. The result depends on the weight of the positive and negative values and how they interact with the
              pixel values in the image.


                            Task                                                         21 st  Century   #Technology Literacy
                                                                                             Skills


                Visit the https://setosa.io/ev/image-kernels/ link and change the value in the given image kernel.

















                Now answer the following questions:
                1.  Make 4 numbers negative. Keep the rest as it is. Write your observation:



                2.  Now, change the center value to negative. Write your observation:


                3.  Now, change the second value of each row to positive. Keep the rest as it is. Write your observation:



                4.  Now, what effect did you apply to final image?






                       What is Neural Network?

              Neural Networks are a series of algorithms used to recognise hidden patterns in raw data, process it, cluster
              and classify it, and continuously learn and improve. They are used in a variety of applications such as predicting
              stock prices, identifying sales and marketing trends, risk assessment, and fraud detection. The main advantage of
              neural network is that the data features can be extracted automatically by the machine without the input from the
              developer. Neural networks are primarily used for solving problems with large datasets, like images.
              A Neural Network is divided into multiple layers and each layer is further divided into several units or neurons,
              also known as nodes Each neuron processes its inputs, applies a mathematical function and passes the result to
              the next layer.

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