NumPy Python Programming Language Library from Scratch A-Z™
NumPy Python Programming Language Library from Scratch A-Z™
NumPy Library for Data Science, Machine Learning,Pandas, Deep Learning using Python from A-Z with the NumPy stack course
Created by Oak Academy, Ali CAVDAR | 4 hours on-demand video course
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.
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
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