Faster Scikit-learn on GPU with NVIDIA cuML - Tutorial and Benchmarks
Python Simplified
@pythonsimplifiedAbout
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! π€ I'm here to help you with your programming journey (in particular - your Python programming journey π) and show you how many beautiful and powerful things we can do with code! πͺπͺπͺ
Video Description
In this step-by-step tutorial, we will explore the Scikit-learn speed boost on GPU, freshly powered by NVIDIA cuML! π 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 isβwe will do it with ZERO CODE CHANGES! Just good old Scikit-Learn, but incredibly faster! πͺπͺπͺ π What Youβll Learn π - 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! π± π‘ Why Watch? π‘ 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. π¨βπ» π― Whoβs This For? π― - Data scientists and ML practitioners using Scikit-Learn π - Anyone curious about GPU-accelerated machine learning π» - Beginners and pros looking to optimize ML workflows π€ π₯ Video Resources π₯ β Simple Machine Learning with Scikit-Learn: https://youtu.be/-IvNzmrcyUM β CUDA Simply Explained: https://youtu.be/r9IqwpMR9TE π¦ Code and Setup Resources π¦ β Official cuML Scikit-learn Colab Notebook: https://nvda.ws/3Yd7Ry4 β Official cuML Scikit-learn Blog: https://nvda.ws/447L1vz β RAPIDS Installation Guide: https://docs.rapids.ai/install β Full Tutorial Code & Benchmark Visualization Notebook on GitHub: https://github.com/MariyaSha/scikit_learn_simplified π Install cuML Scikit-Learn π %load_ext cuml.accel π Have questions or benchmarks? Drop them in the comments! π β° Time Stamps β° 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 Donβt miss out! πLike πSubscribe and π© Share your benchmarks in the comments to join the GPU revolution! Letβs make machine learning faster together! πππ #MachineLearning #ScikitLearn #NVIDIA #cuML #GPU #DataScience #Python #GoogleColab #RandomForest #BigData #MLTutorial #AI #DeepLearning #DataScientist #MLWorkflow #GPUAcceleration @NVIDIADeveloper
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