This lecture talks about 1D and 2D gradient descent mechanisms along with Batch Gradient Descent. The lecture also shows how to get the job done on Python.

⏲Outline⏲
00:00 Introduction
01:42 Learning Rate
02:37 Irregular Function Minimization
03:23 Condition of Global Convergence
04:15 Gradient Descent in 2D
07:44 Gradient Descent Mechanics
11:03 Batch Gradient Descent
12:13 Python: Batch Gradient Descent
13:45 Gradient Descent with Different Learning Rates
22:32 Convergence Rate
24:24 Outro

#pyton #tensorflow #scikit-learn #machine-learning