Optimizing Python Code Speed with Numba JIT Compiler
Offered By: The Machine Learning Engineer via YouTube
Course Description
Overview
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
MongoDB for DBAsMongoDB University Optimizing Performance for SQL Based Applications
Microsoft via edX App Deployment, Debugging, and Performance
Google Cloud via Coursera Application Deployment, Debug, Performance 日本語版
Google Cloud via Coursera Optimize TensorFlow Models For Deployment with TensorRT
Coursera Project Network via Coursera