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amazon-sagemaker-cv

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

aum

awesome-network-analysis

A curated list of awesome network analysis resources.

aws-neuron-samples

Example code for AWS Neuron SDK developers building inference and training applications

awsome-distributed-training

beaker-notebook

Web-based, polyglot research platform.

benchmarks

A benchmark framework for Tensorflow

bertviz

BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

bf16_transformer

bnb_tsp

Travelling Salesman Algorithm using Branch and Bound. Optimized for SSE4.

board_interlocks

Data and analysis related to interlocking directorates among boards of publicly traded companies.

byteps

A high performance and generic framework for distributed DNN training

callbacks

custom callbacks for tensorflow

causaltree

Working repository for Causal Tree and extensions

cocoapi

COCO API - Dataset @ http://cocodataset.org/

colab

Utilities and tests for Google Colab

complete-javascript-course

Starter files, final projects, and FAQ for my Complete JavaScript course

covid_bayes

cpm

Convolutional Pose Machines in TensorFlow

cs505-computational-tools-for-data-science

Repository for CS 505 as taught Fall 2016 in BU Computer Science

datavec

ETL Library for Machine Learning

debugger_demos

decision_tree

Python program for training the decision tree for people detection (based on LBP - Local Binary Patterns) and converting the tree to hardware (FPGA) implementation.

deep-learning-containers

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

deep-learning-models

Deep Learning Models optimized for AWS

deeplearningbook

MIT Deep Learning Book in PDF format

deeplearningexamples

Deep Learning Examples

deepsurv

DeepSurv is a deep learning approach to survival analysis.

diffusers-interpret

Diffusers-Interpret 🤗🧨🕵️‍♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.