<jupyter_start><jupyter_text>Directional Derivative<jupyter_code>import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
def f(x, y):
    return 300 - 2 * (x ** 2) - 3 * (y ** 2)
def df(x, y):
    return np.array([-4 * x, -6 * y])
def df_(x, y, z):
    return np.array([-4 * x, -6 * y, -1])
print(df(4, 9))
print(df_(4, 9, 28))<jupyter_output>[-16 -54  -1]
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '595384', 'license': 'MIT', 'n_tokens_mistral': 187, 'n_tokens_neox': 173, 'n_words': 51, 'path': 'Lesson 03 - Directional Derivative.ipynb', 'repo_name': 'derrowap/MA490-Deep-Learning', 'size': '390'}