[numpy, scipy] Edits and Corrections (#122)

* [numba] trial, please ignore

* [numba] typo

* [scipy] add usful feature of Numpy comparing to other libraries

* [numpy] 11.8 Recursion

* [scipy] Recursion

* [scipy] ammended previous PR

* remove Chapter 16

* Update scipy.md

Co-authored-by: u7062654 <[email protected]>
Co-authored-by: mmcky <[email protected]>
Co-authored-by: John Stachurski <[email protected]>

Author: 4 people

lectures/numba.md

@@ -555,7 +555,7 @@ Now let's see how fast it runs:
 %time calculate_pi()
 ```
 
-If we switch of JIT compilation by removing `@njit`, the code takes around
+If we switch off JIT compilation by removing `@njit`, the code takes around
 150 times as long on our machine.
 
 So we get a speed gain of 2 orders of magnitude--which is huge--by adding four

lectures/scipy.md

@@ -63,7 +63,8 @@ from numpy.fft import fft, ifft
 from numpy.lib.scimath import *
 ```
 
-However, it's more common and better practice to use NumPy functionality explicitly
+However, it's more common and better practice to use NumPy functionality explicitly.
+
 
 ```{code-cell} python3
 import numpy as np
@@ -442,7 +443,7 @@ We leave you to investigate the [set of available routines](http://docs.scipy.or
 (sp_ex1)=
 ### Exercise 1
 
-Previously we discussed the concept of {ref}`recursive function calls <recursive_functions>`.
+In {ref}`this lecture <python_advanced_features>`, we will discuss the concept of {ref}`recursive function calls <recursive_functions>`.
 
 Try to write a recursive implementation of homemade bisection function {ref}`described above <bisect_func>`.