Optimizing Python Code Speed with Numba JIT Compiler
Offered By: The Machine Learning Engineer via YouTube
Course Description
Overview
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Learn to optimize the speed of Python code using the Numba JIT (Just-in-Time) compiler in this 24-minute tutorial. Explore the implementation of jit and njit decorators to enhance code performance, and gain hands-on experience with practical examples provided in the accompanying Jupyter notebook. Discover techniques to significantly improve execution time for computationally intensive tasks, making your Python programs more efficient and responsive.
Syllabus
Optimize speed of your python code with numba JIT (Just in Time) compiler
Taught by
The Machine Learning Engineer
Related Courses
Fundamental Tools of Data WranglingUniversity of Colorado Boulder via Coursera From Python to Numpy
Independent Data Analysis with Python: Zero to Pandas
Jovian Learning MATLAB
LinkedIn Learning NumPy Essential Training: 1 Foundations of NumPy
LinkedIn Learning