Let's start by doing gradient descent by hand. For this, you cannont use any python packages w you should do this using your algebra skills and a calculator, I recommen doing this on pen and paper and then attaching a picture/scan of your work to this python notebook Part 1: Only Estimate Slope For this example, let's assume we are only trying to estimate one variable given one data point. Let's just consider the slope m of a line and one data point x = 1 . For gradient descent, we'll also need a couple of parameters set ahead of time: 1) starting slope, 2) the cost function (and its partial derivative writ the parameter we are trying to estimate), and 3) the step size/learning rate. Let's start with m=3, a cost function cost(m)=m3, and a step size/learning rate =0.5 Using some calculus, the partial derivative of the cost function wr.t. m is sdron=3m2. This derivative is what you will use to calculate the gradient. 1. Using these starting variables and a starting data point of x=1, what is the slope after the first iteration of gradient descent? (HINT: it should be less than 3 ) 2. What is updated slope on the next iteration? and the third iteration? 3. What is happening to the slope after each iteration? is it increasing, decreasing, staying the same