Python NumPy Programming and Project Development using NumPy
- Description
- Curriculum
- FAQ
- Reviews
A warm welcome to the Python NumPy Programming and Project Development using NumPy course by Uplatz.
NumPy stands for Numerical Python and it is a core scientific computing library in Python. NumPy provides efficient multi-dimensional array objects and various operations to work with these array objects.
NumPy is a Python library used for working with arrays. It also has functions for working in domain of linear algebra, fourier transform, and matrices. NumPy was created in 2005 by Travis Oliphant. It is an open source project and you can use it freely. NumPy is written partially in Python, but most of the parts that require fast computation are written in C or C++.
Purpose of using NumPy
In Python we have lists that serve the purpose of arrays, but they are slow to process. NumPy aims to provide an array object that is up to 50x faster than traditional Python lists. The array object in NumPy is called ndarray, it provides a lot of supporting functions that make working with ndarray very easy. Arrays are very frequently used in data science, where speed and resources are very important.
NumPy arrays are stored at one continuous place in memory unlike lists, so processes can access and manipulate them very efficiently. This behavior is called locality of reference in computer science. This is the main reason why NumPy is faster than lists. Also it is optimized to work with latest CPU architectures.
NumPy is essentially a library consisting of multidimensional array objects and a collection of routines for processing those arrays. Using NumPy, mathematical and logical operations on arrays can be performed.
NumPy lies at the core of a rich ecosystem of data science libraries. A typical exploratory data science workflow might look like:
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Extract, Transform, Load: Pandas, Intake, PyJanitor
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Exploratory analysis: Jupyter, Seaborn, Matplotlib, Altair
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Model and evaluate: scikit-learn, statsmodels, PyMC3, spaCy
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Report in a dashboard: Dash, Panel, Voila
Features of NumPy
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POWERFUL N-DIMENSIONAL ARRAYS
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Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today.
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NUMERICAL COMPUTING TOOLS
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NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.
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INTEROPERABLE
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NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.
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PERFORMANT
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The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.
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EASY TO USE
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NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level.
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OPEN SOURCE
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Distributed under a liberal BSD license, NumPy is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community.
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Using NumPy, a developer can perform the following operations −
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Mathematical and logical operations on arrays.
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Fourier transforms and routines for shape manipulation.
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Operations related to linear algebra. NumPy has in-built functions for linear algebra and random number generation.
Uplatz provides this in-depth training on Python programming using NumPy. This NumPy course explains the concepts & structure of NumPy including its architecture and environment. The course discusses the various array functions, types of indexing, etc. and moves on to using NumPy for creating and managing multi-dimensional arrays with functions and operations. This Python NumPy course also discusses the practical implementation of NumPy to develop prediction models & projects.
NumPy Python Programming and Project Development using NumPy – Course Syllabus
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INTRODUCTION TO NUMPY
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NUMPY TUTORIAL BASICS
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NUMPY ATTRIBUTES AND FUNCTIONS
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CREATING ARRAYS FROM EXISTING DATA
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CREATING ARRAYS FROM RANGES
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INDEXING AND SLICING IN NUMPY
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ADVANCED SLICING IN NUMPY
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APPEND AND RESIZE FUNCTIONS
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NDITER AND BROADCASTING
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NUMPY BROADCASTING
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NDITER FUNCTION
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ARRAY MANIPULATION FUNCTIONS
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NUMPY UNIQUE()
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NUMPY DELETE()
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NUMPY INSERT FUNCTION
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NUMPY RAVEL AND SWAPAXES()
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SPLIT FUNCTION
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HSPLIT FUNCTION
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VSPLIT FUNCTION
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LEFTSHIFT AND RIGHTSHIFT FUNCTIONS
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NUMPY TRIGONOMETRIC FUNCTIONS
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NUMPY ROUND FUNCTIONS
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NUMPY ARITHMATIC FUNCTIONS
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NUMPY POWER AND RECIPROCAL FUNCTIONS
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NUMPY MOD FUNCTION
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NUMPY IMAG() AND REAL() FUNCTIONS
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NUMPY CONCATENATE()
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NUMPY STATISTICAL FUNCTIONS
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STATISTICAL FUNCTIONS
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NUMPY AVERAGE FUNCTION
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NUMPY SEARCH SORT FUNCTIONS
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SORT FUNCTION
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NUMPY SORT FUNCTION
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NUMPY ARGSORT()
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NONZERO AND WHERE FUNCTIONS
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EXTRACT FUNCTION
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NUMPY ARGMAX ARGMIN()
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BYTESWAP COPIES AND VIEWS
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NUMPY STRING FUNCTIONS
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NUMPY CENTER FUNCTION
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CAPITALIZE AND CENTER()
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NUMPY TITLE FUNCTION
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STRING FUNCTIONS
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NUMPY MATRIX LIBRARY
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NUMPY JOIN ARRAYS
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LINEAR ALGEBRA
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RANDOM MODULE
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SECRETS MODULE
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RANDOM MODULE UNIFORM FUNCTION
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RANDOM MODULE GENERATE NUMBER EXCEPT K
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SECRETSMODULE GENERATE TOKENS
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RANDOM MODULE GENERATE BINARY STRING
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NUMPY MODULE REVISE
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NUMPY INDEXING
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NUMPY BASIC OPERATIONS
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NUMPY UNARY OPERATORS
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BINARY OPERATORS IN NUMPY
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NUMPY UNIVERSAL FUNCTIONS
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NUMPY FILTER ARRAYS
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NUMPY MODULE PROJECTS
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14Array Manipulation FunctionsVideo lesson
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15NumPy Unique()Video lesson
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16NumPy Delete() - part 1Video lesson
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17NumPy Delete() - part 2Video lesson
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18NumPy Insert FunctionVideo lesson
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19Numpy RAVEL() SWAPAXES()Video lesson
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20SPLIT FunctionVideo lesson
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21HSPLIT()Video lesson
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22VSPLIT()Video lesson
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23LEFT Shift and RIGHT Shift FunctionsVideo lesson
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24NumPy Trigonometric FunctionsVideo lesson
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25NumPy Round FunctionsVideo lesson
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26NumPy Arithmetic FunctionsVideo lesson
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27NumPy Power and Reciprocal FunctionsVideo lesson
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28NumPy Power and Mod FunctionsVideo lesson
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29NumPy IMAG() REAL()Video lesson
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56Random Module - part 1Video lesson
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57Random Module - part 2Video lesson
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58Random Module - part 3Video lesson
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59Random Module - part 4Video lesson
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60Random Module - part 5Video lesson
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61Random Module - part 6Video lesson
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62Random Module - part 7Video lesson
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63Random Module - part 8Video lesson
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64Random Module - part 9Video lesson
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65Random Module - part 10Video lesson
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66Random Module - part 11Video lesson
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67Random Module - part 12Video lesson
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68Random Module - part 13Video lesson
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69Random Module - part 14Video lesson
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70Random Module - part 15Video lesson
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71Random Module - part 16Video lesson
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72Random Module - part 17Video lesson
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73Random Module - part 18Video lesson
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74Random Module - part 19Video lesson
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75Secrets Module - part 1Video lesson
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76Secrets Module - part 2Video lesson
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77Random Module Uniform FunctionVideo lesson
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78Random Module Generate Number Except KVideo lesson
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79Secrets Module Generate TokensVideo lesson
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80Random Module Generate Binary StringVideo lesson
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