Faster Scikit-learn on GPU with NVIDIA cuML - Tutorial and Benchmarks

Python Simplified β€’ May 5, 2025
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Python Simplified

@pythonsimplified

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Hi everyone! My name is Mariya and I'm a software developer from Sofia, Bulgaria. I film programming tutorials about Computer Science Concepts, GUI Applications, Machine Learning and Artificial Intelligence, Automation and Web Scraping, Data Science and even Math! πŸ€“ I'm here to help you with your programming journey (in particular - your Python programming journey πŸ˜‰) and show you how many beautiful and powerful things we can do with code! πŸ’ͺπŸ’ͺπŸ’ͺ

Video Description

In this step-by-step tutorial, we will explore the Scikit-learn speed boost on GPU, freshly powered by NVIDIA cuML! πŸš€ Using a free GPU on Google Colab, and a local RTX 4080, we will perform CPU versus GPU speed tests, gradually increasing the complexity, and exploring the performance gap. The best part isβ€”we will do it with ZERO CODE CHANGES! Just good old Scikit-Learn, but incredibly faster! πŸ’ͺπŸ’ͺπŸ’ͺ πŸ“š What You’ll Learn πŸ“š - How to set up cuML on Google Colab (using a FREE Tesla T4 GPU) - How to set up cuML on your local system. - When GPUs crush CPUs for big datasets - 3 use cases code demo! - Real-world benchmarks: CPU vs. GPU speed tests on my LEGION and ROG systems, including a 53-minute CPU run vs. 87-second GPU run! 😱 πŸ’‘ Why Watch? πŸ’‘ This video will show you how to save hours on training and optimization without rewriting even a single line in your Scikit-Learn code!!! It's also perfect for anyone working with large datasets or intensive algorithms! Plus, I share my benchmarking code on GitHub for you to try on your system, and visualize it alongside mine. πŸ‘¨β€πŸ’» 🎯 Who’s This For? 🎯 - Data scientists and ML practitioners using Scikit-Learn 🐍 - Anyone curious about GPU-accelerated machine learning πŸ’» - Beginners and pros looking to optimize ML workflows πŸ€– πŸŽ₯ Video Resources πŸŽ₯ ⭐ Simple Machine Learning with Scikit-Learn: https://youtu.be/-IvNzmrcyUM ⭐ CUDA Simply Explained: https://youtu.be/r9IqwpMR9TE πŸ“¦ Code and Setup Resources πŸ“¦ ⭐ Official cuML Scikit-learn Colab Notebook: https://nvda.ws/3Yd7Ry4 ⭐ Official cuML Scikit-learn Blog: https://nvda.ws/447L1vz ⭐ RAPIDS Installation Guide: https://docs.rapids.ai/install ⭐ Full Tutorial Code & Benchmark Visualization Notebook on GitHub: https://github.com/MariyaSha/scikit_learn_simplified 🐍 Install cuML Scikit-Learn 🐍 %load_ext cuml.accel πŸ’Œ Have questions or benchmarks? Drop them in the comments! πŸ’Œ ⏰ Time Stamps ⏰ 01:04 - setup cuML sklearn in Google Colab 01:57 - setup cuML sklearn locally 03:23 - what workflows are better for GPU? 03:47 - use GPU for giant datasets 07:29 - use GPU for complex algorithms 11:17 - CPU vs GPU benchmark charts 11:40 - cuML vs sklearn accuracy 12:29 - use GPU for giant datasets and complex algorithms 13:12 - advanced CPU vs GPU benchmark charts Don’t miss out! πŸ‘Like πŸ””Subscribe and πŸ“© Share your benchmarks in the comments to join the GPU revolution! Let’s make machine learning faster together! πŸš€πŸš€πŸš€ #MachineLearning #ScikitLearn #NVIDIA #cuML #GPU #DataScience #Python #GoogleColab #RandomForest #BigData #MLTutorial #AI #DeepLearning #DataScientist #MLWorkflow #GPUAcceleration @NVIDIADeveloper

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