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MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 25 lectures (4h 17m) | Size: 1.63 GB
Numpy for data analytics, python numpy
What you'll learn
Python numpy: The numerical array to store data
Attributes of numpy and their usage
Creation of array by using different routines
Usage of numpy
Use of numpy with matDescriptionlib
Requirements
Python programming
Description
The data analytics needs specialized data structure for storing numerical data. The numpy library provides the required data stucture. NumPy is a Python package. It stands for 'Numerical Python'. It is a library consisting of multidimensional array objects and a collection of routines for processing of array. In this course python numpy library is explained in details. In this tutorial you will learn,
What is numpy?
How to create and use numpy array?
Accessing elements of array.
Operations on numpy array.
Functions of numpy array.
Anybody knowing basic knowledge of python programming can take up this course. In this course each and every concept is explained in detail. Also following resources are provided to students,
Notes
Examples
The contents of this course are,
1. What is numpy
2. How to install numpy
3. NumPy - Ndarray Object
4. NumPy - Data Types
5. NumPy - Array Attributes
6. NumPy - Array Creation Routines
7. NumPy - Array From Existing Data
8. NumPy - Array From Numerical Ranges
9. NumPy - Indexing & Slicing
10. NumPy - Advanced Indexing
11. NumPy - Broadcasting
12. NumPy - Iterating Over Array
13. NumPy - Array Manipulation
14. NumPy - Binary Operators
15. NumPy - String Functions
16. NumPy - Mathematical Functions
17. NumPy - Arithmetic Operations
18. NumPy - Statistical Functions
19. NumPy - Sort, Search & Counting Functions
20. NumPy - Byte Swapping
21. NumPy - Copies & Views
22. NumPy - Matrix Library
23. NumPy - Linear Algebra
24. NumPy - MatDescriptionlib
25. NumPy - Histogram Using MatDescriptionlib
26. I/O with NumPy
Who this course is for
Under graduate, post graduate students, working professional, aspiring data analyst/scientist
Homepage
Code:
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