aamini/introtodeeplearning
Lab Materials for MIT 6.S191: Introduction to Deep Learning

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Lab Materials for MIT 6.S191: Introduction to Deep Learning

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Contains some old pages from python.org

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igneous 🌿

Python cloud pipeline for Neuroglancer compatible Downsampling, Meshing, Skeletonizing, Remapping, and more.

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This is the sample code for the Introduction to Tornado book, published by O'Reilly Media.

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intro-to-dl 🌿

Introduction to deep learning

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XenonPy 🌿

XenonPy is a Python Software for Materials Informatics

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once-for-all 🌿

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

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Materials for a Deep Learning Workshop

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torchprofile 🌿

A more general and accurate MACs / FLOPs profiler for PyTorch models

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Lectures for INFO8006 - Introduction to Artificial Intelligence, ULiège

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amc 🌿

[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices

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haq 🌿

[CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision

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VWW 🌿

First place in the Visual Wake Words challenge (TF-lite track) in LPIRC'19

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dlg 🌿

[NeurIPS 2019] Deep Leakage From Gradients

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pvcnn 🌿

[NeurIPS 2019, Spotlight] Point-Voxel CNN for Efficient 3D Deep Learning

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