如何确定学习速率和方差的梯度下降算法?

I started to learn the machine learning last week. when I want to make a gradient descent script to estimate the model parameters, I came across a problem: How to choose a appropriate learning rate and variance。I found that，different (learning rate，variance) pairs may lead to different results, some times you even can't convergence. Also, if change to another training data set, a well-chose （learning rate，variance）pair probably will not work. For example(script below)，when I set the learning rate to 0.001 and variance to 0.00001, for 'data1', I can get the suitable theta0_guess and theta1_guess. But for ‘data2’, they can't make the algorithem convergence, even when I tried dozens of （learning rate，variance）pairs still can't reach to convergence. I started to learn the machine learning last we