Implementation of machine learning at Hackveda .

NumPy
let us have a glimpse what numpy is :
NumPy is a mathematical library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
Using numpy, mathematical and logical operations on arrays can be performed.
NumPy is an N-Dimensional arrat type called ‘ndarray’ . This ndarray describes the collection of items of same type .
Every element in a ndarray is an object of data type object called ‘dtype’.
FUNCTIONS used in numpy are :
- Identity
- Astype
- Arange
- Linspace
- Indices
- Data types
- Reshape function
- Converting list into an array
- Slicing
- Transpose
Firstly we will import numpy :

IDENTITY

In identity matrix values are printed in float .
ASTYPE

In Astype , they are used to convert its data type like integer to float and vice versa .
ARANGE

- In Arange , it will print values in order exluding the last number i.e it will print n-1 numbers .

- data type of integer is changed
LINSPACE

- In linspace , its returns number spaces . it creates matrix with intervals according to the num mentioned .
INDICES

- In Indices , it prints the indexes of the matrix first and then the values of the matrix .
DATA TYPES

- In data types , it will tell you the type of array using ‘dtype’ .

Format to change the type of array used .
RESHAPE

- Reshape , it will reshape the list of elements you mentioned above into a matrix you want .

- You just have to write elements in row form in type of matrix you need .
CONVERSION OF LIST INTO AN ARRAY

- In this coversion of list into an array , using numpy list can simply be converted into an array .
SLICING

- Slicing helps you to print particular part of the array .
- You have to mention index of the items and they are separated by colan(:)
- (0:5:2) or (2::2) → another colan or double colan represents the gap you need to print between the items .
TRANSPOSE

- Transpose will convert the rows into columns and vice versa of the matrix mentioned above .
So this is all you need to know to use NumPy .
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