Python NumPy Course For Data Science And Machine Learning
Deep Learning Prerequisites: The Numpy Stack in Python
Lectures -11
Resources -1
Duration -1 hours
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Course Description
Welcome! This is Deep Learning, Machine Learning, and Data Science Prerequisites: The Numpy Stack in Python.
One question or concern I get a lot is that people want to learn deep learning and data science, so they take these courses, but they get left behind because they don’t know enough about the Numpy stack in order to turn those concepts into code.
Even if I write the code in full, if you don’t know Numpy, then it’s still very hard to read.
This course is designed to remove that obstacle - to show you how to do things in the Numpy stack that are frequently needed in deep learning and data science.
So what are those things?
Numpy. This forms the basis for everything else. The central object in Numpy is the Numpy array, on which you can do various operations.
The key is that a Numpy array isn’t just a regular array you’d see in a language like Java or C++, but instead is like a mathematical object like a vector or a matrix.
That means you can do vector and matrix operations like addition, subtraction, and multiplication.
The most important aspect of Numpy arrays is that they are optimized for speed. So we’re going to do a demo where I prove to you that using a Numpy vectorized operation is faster than using a Python list.
Then we’ll look at some more complicated matrix operations, like products, inverses, determinants, and solving linear systems.
Goals
What will you learn in this course:
- Basics of Numpy, Arrays, Lists.
- Accessing/Changing Specific Elements, Rows, Columns, etc
- Initializing Different Arrays (1s, 0s, full, random, etc)
- Basic Mathematics (arithmetic, trigonometry, etc.)
- Linear Algebra and Statistics
- Reorganizing Arrays
- Load data in from a file
- Advanced Indexing and Boolean Masking
Prerequisites
What are the prerequisites for this course?
- Basics of Python programming languages
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
1 Lectures
- Introduction 02:42 02:42
NumPy and it's Applications
1 Lectures
Basics of NumPy
1 Lectures
NumPy Datatypes
1 Lectures
Accessing/Changing Specific Elements, Rows, Columns, etc
1 Lectures
Initializing Different Arrays (1s, 0s, full, random, etc)
1 Lectures
Basic Mathematics (arithmetic, trigonometry, etc.)
1 Lectures
Linear Algebra and Statistics
1 Lectures
Reorganizing Arrays
1 Lectures
Load data in from a file
1 Lectures
Advanced Indexing and Boolean Masking
1 Lectures
Instructor Details
ADITYA
I have working experience of Web developer of more than three years. I create videos on SQL, Big query, Data Science, Data Analysis, Python, Machine Learning, Deep Learning. I hope you get some value from this channel. If you do please consider subscribing to the channel and share videos with others.
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