Hello tensorflow

We have to figure out the "features" of the secret formula that generated the data we were given, so that we can learn them. In my opinion, this is like 80% of the complexity of solving an ML problem. In this example, we were told the shape of the secret formula (it's a cubic!), so the features we have to learn are the coefficients in the polynomial. For something more complex like the "is this a dog or a blueberry muffin" problem, we'd have to look at pixels and colours and formations and what makes a dog a dog and not a muffin. Once we figure out these features (in our case, those a,b,c,d coefficients), we initialize them to some random values.