If you're looking to grow your career in machine learning or data science in this day and age, adding a powerful library to your skill set is an important place to start. In that vein, Python has become one of the most widely used tools in the industry for serious data analytics, and NumPy is probably the most widely used data analytics library. With NumPy, you can manipulate data involving multi-dimensional arrays and matrices (think linear algebra).
Join us as we venture into the vast world of NumPy in this comprehensive course. Each lesson dive into the actual implementation of concepts in both pure Python and then NumPy, exploring how NumPy vectorization compares to traditional Python that uses a procedural and object-oriented approach.
Practice and test yourself along the way with in-browser coding challenges, quizzes, and more.
This course is intended for users who are already familiar with intermediate level Python.
If you're looking to grow your career in machine learning or data science in this day and age, adding a powerful library to your...Show More
Content
1.
Introduction
7 Lessons
Get familiar with NumPy fundamentals, including array creation, reshaping, indexing, and vectorization.
2.
Anatomy of an Array
5 Lessons
Look at the foundational elements of NumPy arrays, memory layout, views, copies, and optimization.
3.
Code Vectorization
13 Lessons
Examine methods to enhance Python code efficiency using NumPy for various simulations.
4.
Problem Vectorization
9 Lessons
Find out about problem vectorization to enhance algorithmic efficiency in Python and NumPy.
5.
Custom Vectorization
5 Lessons
Dig into custom vectorization techniques using Typed Lists and memory-aware NumPy arrays.
6.
Beyond NumPy
4 Lessons
Implement optimized Python techniques and explore advanced libraries beyond NumPy for enhanced performance.
7.
Conclusion
2 Lessons
Master the steps to effectively leverage NumPy for creative and efficient problem-solving.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
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