Question: Make it clear please. A) Handwritten Digit Recognition MNIST dataset (5 marks) The MNIST dataset is a well-known dataset in machine learning. Based on your

Make it clear please.
A) Handwritten Digit Recognition MNIST dataset (5 marks) The MNIST dataset is a well-known dataset in machine learning. Based on your internet search, summarize the MNIST dataset and the problem to solve. Make sure you include the reference to show where you obtain this information. B) MODEL 1 1. Documentation in Code (10 marks) Analyze each code and add comments by using your own words. The comment must be clear, and they aim to help others understand the code well. This task is essential to show your understanding of the code. Please consider explaining line by line the given codes. 2. Draw/Sketch the neural network structure (10 marks) Analyze the code and draw/sketch the diagram of the network structure. E.g. Outputs (X outputs) Hidden Layers (y neurons) Input Layers (y inputs) Fig. 1: Example Model x Network Structure To obtain the model architecture, you may add a model visualizer into the code, such as in Keras plot_model A) Handwritten Digit Recognition MNIST dataset (5 marks) The MNIST dataset is a well-known dataset in machine learning. Based on your internet search, summarize the MNIST dataset and the problem to solve. Make sure you include the reference to show where you obtain this information. B) MODEL 1 1. Documentation in Code (10 marks) Analyze each code and add comments by using your own words. The comment must be clear, and they aim to help others understand the code well. This task is essential to show your understanding of the code. Please consider explaining line by line the given codes. 2. Draw/Sketch the neural network structure (10 marks) Analyze the code and draw/sketch the diagram of the network structure. E.g. Outputs (X outputs) Hidden Layers (y neurons) Input Layers (y inputs) Fig. 1: Example Model x Network Structure To obtain the model architecture, you may add a model visualizer into the code, such as in Keras plot_model
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