Visualizing Linear Regression with #pytorch

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Linear regression is a common machine learning technique that predicts a real-valued output using a weighted linear combination of one or more input values.For instance, the sale price of a house can often be estimated using a linear combination of features such as area, number of bedrooms, number of floors, date of construction etc. Mathematically, it can be expressed using the following equation:house_price = w1 ** area + w2 ** n_bedrooms + w3 ** n_floors + ... + w_n ** age_in_years + bThe “learning” part of linear regression is to figure out a set of weights w1, w2, w3, ... w_n, b that leads to good predictions. This is done by looking at lots of examples one by one (or in batches) and adjusting the weights slightly each time to make better predictions, using an optimization technique (...)