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You can now download the source code that sparked the AI boom

Flipboard

On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet , the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 by proving that "deep learning" could achieve things conventional AI techniques could not.

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Build ETL Pipelines for Data Science Workflows in About 30 Lines of Python

KDnuggets

Well grab data from a CSV file (like youd download from an e-commerce platform), clean it up, and store it in a proper database for analysis. In the real world, you might be downloading this CSV from your e-commerce platforms reporting dashboard, pulling it from an FTP server, or getting it via API.

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10 GitHub Awesome Lists for Data Science

Flipboard

It is ideal for data science projects, machine learning experiments, and anyone who wants to work with real-world data. After Kaggle, this is one of the best sources for free datasets to download and enhance your data science portfolio. Perfect for hands-on learners who want to deepen their understanding through practical examples.

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Deploy Gradio Apps on Hugging Face Spaces

PyImageSearch

Jump Right To The Downloads Section Need Help Configuring Your Development Environment? Once both files are created and populated, the Space will automatically start downloading dependencies, and then build and launch our app. Looking for the source code to this post? Having trouble configuring your development environment?

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Implementing Approximate Nearest Neighbor Search with KD-Trees

PyImageSearch

This lesson is the 1st in a 2-part series on Mastering Approximate Nearest Neighbor Search : Implementing Approximate Nearest Neighbor Search with KD-Trees (this tutorial) Approximate Nearest Neighbor with Locality Sensitive Hashing (LSH) To learn how to implement an approximate nearest neighbor search using KD-Tree , just keep reading.

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Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection

PyImageSearch

For example: * Running on local URL: [link] * Running on public URL: [link] Downloading [link] to 'yolov12s.pt'. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Create a new conda environment with Python 3.11: conda create -n yolov12 python=3.11

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PEFT fine tuning of Llama 3 on SageMaker HyperPod with AWS Trainium

AWS Machine Learning Blog

Trainium chips are purpose-built for deep learning training of 100 billion and larger parameter models. Model training on Trainium is supported by the AWS Neuron SDK, which provides compiler, runtime, and profiling tools that unlock high-performance and cost-effective deep learning acceleration. architectures/5.sagemaker-hyperpod/LifecycleScripts/base-config/

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