```python
import sympy as sm
from scipy.misc import derivative
```


```python
x, y, z = sm.symbols('x y z')
```


```python
#Function - 3x**2
sm.diff(3*x**2)
```




$\displaystyle 6 x$




```python
sm.diff(2*x)
```




$\displaystyle 2$




```python
def myFunc(x):
    return 2*x
```


```python
derivative(myFunc,4)
```




    2.0




```python
#Function 3x^2+5x
sm.diff(3*x**2+5*x)
```




$\displaystyle 6 x + 5$




```python
#Product Rule
sm.diff((x**2 + 1) * sm.cos(x))
```




$\displaystyle 2 x \cos{\left(x \right)} - \left(x^{2} + 1\right) \sin{\left(x \right)}$




```python
#Chain Rule
sm.diff((x**2 - 3*x + 5) ** 3)
```




$\displaystyle \left(6 x - 9\right) \left(x^{2} - 3 x + 5\right)^{2}$




```python
#Partial Derivative
f = x**2 * y * z**5
```


```python
sm.diff(f,x)
```




$\displaystyle 2 x y z^{5}$




```python
sm.diff(f,y)
```




$\displaystyle x^{2} z^{5}$




```python
sm.diff(f,z)
```




$\displaystyle 5 x^{2} y z^{4}$




```python

```

45adf8f26f8d89789afdf766faeca9657fde2924
ipynb
Jupyter Notebook
Multivariate Calculus.ipynb
perceptrons-ai/Computational-Mathematics
ffb88b4de735735696eba652eee24c24758f33cd
MIT
2021-02-23T05:37:30.000Z
2021-02-23T05:37:30.000Z
Multivariate Calculus.ipynb
perceptrons-ai/Computational-Mathematics
ffb88b4de735735696eba652eee24c24758f33cd
MIT
Multivariate Calculus.ipynb
perceptrons-ai/Computational-Mathematics
ffb88b4de735735696eba652eee24c24758f33cd
MIT
Qwen/Qwen-72B
1. YES
2. YES