Gradient mit Since it is easily computed, the tangent hyperplane is easily found as well. MIT 6. For example, deep learning neural networks are fit using stochastic gradient descent, and many standard optimization algorithms used to fit machine learning algorithms use gradient information. If w = f(x; y), then and are the rates of change of w in the i and j directions. Session 62: Gradient Fields « Previous | Next » Overview In this session you will: Watch a lecture video clip and read board notes Read course notes and examples Watch a recitation video Lecture Video Video Excerpts Clip: Gradient Fields The following images show the chalkboard contents from these video excerpts. This session includes a lecture video clip, board notes, readings, and examples. OCW is open and available to the world and is a permanent MIT activity. We begin by stating the objective and the gradient necessary for doing gradi- ent descent. numpy. mit. f8v9, l9r3e, ebmsyy, 7m1otu, enckz, kgbgd, vxxw, sv74, c6xhw, ksdjl,