Published 08/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 37 lectures (3h 46m) | Size: 949.7 MB
NumPy Library for Data Science, Machine Learning,Pandas, Deep Learning using Python from A-Z with the NumPy stack course
What you’ll learn
Installing Anaconda Distribution for Windows
Installing Anaconda Distribution for MacOs
Installing Anaconda Distribution for Linux
Introduction to NumPy Library
The Power of NumPy
Creating NumPy Array with The Array() Function
Creating NumPy Array with Zeros() Function
Creating NumPy Array with Ones() Function
Creating NumPy Array with Full() Function
Creating NumPy Array with Arange() Function
Creating NumPy Array with Eye() Function
Creating NumPy Array with Linspace() Function
Creating NumPy Array with Random() Function
Properties of NumPy Array
Reshaping a NumPy Array: Reshape() Function
Identifying the Largest Element of a Numpy Array: Max(), Argmax() Functions
Detecting Least Element of Numpy Array: Min(), Argmin() Functions
Concatenating Numpy Arrays: Concatenate() Function
Splitting One-Dimensional Numpy Arrays: The Split() Function
Splitting Two-Dimensional Numpy Arrays: Split(), Vsplit, Hsplit() Function
Sorting Numpy Arrays: Sort() Function
Indexing Numpy Arrays
Slicing One-Dimensional Numpy Arrays
Slicing Two-Dimensional Numpy Arrays
Assigning Value to One-Dimensional Arrays
Assigning Value to Two-Dimensional Array
Fancy Indexing of One-Dimensional Arrrays
Fancy Indexing of Two-Dimensional Arrrays
Combining Fancy Index with Normal Indexing
Combining Fancy Index with Normal Slicing
Fancy Indexing of One-Dimensional Arrrays
Fancy Indexing of Two-Dimensional Arrrays
Combining Fancy Index with Normal Indexing
Combining Fancy Index with Normal Slicing
Requirements
No prior knowledge of Numpy is required
Free software and tools used during the course
Basic computer knowledge
Desire to learn Python and Numpy library
Nothing else! It’s just you, your computer and your ambition to get started today
Desire to learn data science
Desire to learn Python
Desire to work on machine learning
Desire to learn python machine learning A-Z
Description
Description
Hello there,
Welcome to “NumPy Python Programming Language Library from Scratch A-Z™” Course
NumPy Library for Data Science, Machine Learning,Pandas, Deep Learning using Python from A-Z with the NumPy stack course
Numpy is a 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. Moreover, Numpy forms the foundation of the Machine Learning stack.
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, numpy stack, numpy python, scipy, Python numpy, deep learning, artificial intelligence, lazy programmer, pandas, machine learning, Data Science, Pandas, Deep Learning, machine learning python, numpy course
POWERFUL N-DIMENSIONAL ARRAYS: Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today.
NUMERICAL COMPUTING TOOLS: NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.
INTEROPERABLE: NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.
PERFORMANT: The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.
EASY TO USE: NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level.
OPEN SOURCE: Distributed under a liberal BSD license, NumPy is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community.
Nearly every scientist working in Python draws on the power of NumPy.
NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.
OAK Academy offers highly-rated data science courses that will help you learn how to visualize and respond to new data, as well as develop innovative new technologies. Whether you’re interested in machine learning, data mining, or data analysis, Udemy has a course for you.
Data science is everywhere. Better data science practices are allowing corporations to cut unnecessary costs, automate computing, and analyze markets. Essentially, data science is the key to getting ahead in a competitive global climate.
Python Numpy, Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels.
Whether you work in machine learning or finance, or are pursuing a career in web development or data science, Python is one of the most important skills you can learn. Python’s simple syntax is especially suited for desktop, web, and business applications. Python’s design philosophy emphasizes readability and usability. Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization.
The core programming language is quite small and the standard library is also large. In fact, Python’s large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks.
Are you ready for a Data Science career?
Do you want to learn the Python Numpy from Scratch? or
Are you an experienced Data scientist and looking to improve your skills with Numpy!
In both cases, you are at the right place! The number of companies and enterprises using Python is increasing day by day. The world we are in is experiencing the age of informatics. Python and its Numpy library will be the right choice for you to take part in this world and create your own opportunities,
In this course, we will open the door of the Data Science world and will move deeper. You will learn the fundamentals of Python and its beautiful library Numpy step by step with hands-on examples. Most importantly in Data Science, you should know how to use effectively the Numpy library. Because this library is limitless.
Throughout the course, we will teach you how to use Python in Linear Algebra and we will also do a variety of exercises to reinforce what we have learned in this Data Science Using Python Programming Language: NumPy Library | A-Z™ course.
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