NumPy for Data Science and Machine Learning in Python
Deep Learning Prerequisites: The Numpy Stack in Python
Updated on Sep, 2023
Language - English
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.
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
What are the prerequisites for this course?
- Basics of Python programming languages
Check out the detailed breakdown of what’s inside the course
- Introduction 02:42 02:42
NumPy and it's Applications
Basics of NumPy
Accessing/Changing Specific Elements, Rows, Columns, etc
Initializing Different Arrays (1s, 0s, full, random, etc)
Basic Mathematics (arithmetic, trigonometry, etc.)
Linear Algebra and Statistics
Load data in from a file
Advanced Indexing and Boolean Masking
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.
User your certification to make a career change or to advance in your current career. Salaries are among the highest in the world.
Our students work
with the Best
Related Video CoursesView More
Become a valued member of Tutorials Point and enjoy unlimited access to our vast library of top-rated Video CoursesSubscribe now
Master prominent technologies at full length and become a valued certified professional.Explore Now