mahwiah Goto Github PK

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Name: Mahwish

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Mahwish's Projects

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

aws-cdk

The AWS Cloud Development Kit is a framework for defining cloud infrastructure in code

aws-glue-samples

AWS Glue code samples

aws-neuron-sdk

Powering Amazon custom machine learning chips. Blazing fast and cost effective, natively integrated into PyTorch and TensorFlow and integrated with your favorite AWS services

aws-step-functions-data-science-sdk-python

Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS

beyond-jupyter-mooc

All the material from the Udemy course "Beyond Jupyter Notebooks"

cntk

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

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-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

fashion-mnist

A MNIST-like fashion product database. Benchmark :point_down:

fasttext

Library for fast text representation and classification.

hacker-scripts

Based on a true story

horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

hyperas

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

hyperopt

Distributed Asynchronous Hyperparameter Optimization in Python

incubator-mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

jupyter

Jupyter metapackage for installation, docs and chat

kaggle-api

Official Kaggle API

keras

Deep Learning for humans

keras-metrics

Metrics for Keras. DEPRECATED since Keras 2.3.0

learn-amazon-sagemaker

Learn Amazon SageMaker

mleap

MLeap: Deploy ML Pipelines to Production

multi-model-server

Multi Model Server is a tool for serving neural net models for inference

neo-ai-dlr

Neo-AI-DLR is a common runtime for machine learning models compiled by AWS SageMaker Neo, TVM, or TreeLite.

sagemaker-chainer-container

Docker container for running Chainer scripts to train and host Chainer models on SageMaker

sagemaker-containers

WARNING: This package has been deprecated. Please use the SageMaker Training Toolkit for model training and the SageMaker Inference Toolkit for model serving.

sagemaker-debugger

Amazon SageMaker Debugger provides functionality to save tensors during training of machine learning jobs and analyze those tensors

sagemaker-inference-toolkit

Serve machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.

sagemaker-mxnet-inference-toolkit

Toolkit for allowing inference and serving with MXNet in SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.com/aws/deep-learning-containers.

sagemaker-mxnet-training-toolkit

Toolkit for running MXNet training scripts on SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.com/aws/deep-learning-containers.

mahwiah Goto Github PK

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