hello, you can find the requirements bellow, i need the code in ipynb file
Grab a “regression” dataset from the UCI archive: edu/ml/datasets.php” target=”_blank” class=”external” rel=”noreferrer noopener”>https://archive.ics.uci.edu/ml/datasets.php (Links to an external site.) or these datasets: https://college.cengage.com/mathematics/brase/understandable_statistics/7e/students/datasets/slr/frames/frame.html (Links to an external site.) Do not use the same dataset as anyone else, i.e., pick randomly.
Choose a single input variable and output variable, and graph their relationship (scatter plot). The plot does not need to look “linear,” since we can find a linear regression line for any data.
Then create a single-neuron network (Linear type neuron) and train the network on the data. Also use the linear regression function of sklearn to find the actual best regression line. Then plot the network’s predictions and sklearn’s predictions on a scatter plot with the original data.
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