vdabravolski

aiops-materials

public materials related to AIOps domain

amazon-sagemaker-examples

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

cucumber-jvm

Cucumber for the JVM (successor of Cuke4Duke)

deepspeed-on-aws

detectron2-sagemaker

Port of Detectron2 to train/deploy model on Amazon Sagemaker

flair-sagemaker-samples

Mask-RCNN-EKS

Running Mask-RCNN using Sagemaker Operators for EKS

MLCourseProject

This is a course project for Coursera's "Practical Machine Learning".

mmdetection-sagemaker

Training MMDetection CV models on AWS Sagemaker platform

mxnet-distributed-sample

example of distributed multi-node/multi-device training of MXNet model

vdabravolski/detectron2-sagemaker

Port of Detectron2 to train/deploy model on Amazon Sagemaker

vdabravolski/mmdetection-sagemaker

Training MMDetection CV models on AWS Sagemaker platform

vdabravolski/deepspeed-on-aws

vdabravolski/aiops-materials

public materials related to AIOps domain

vdabravolski/amazon-sagemaker-examples

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

vdabravolski/flair-sagemaker-samples

vdabravolski/mxnet-distributed-sample

example of distributed multi-node/multi-device training of MXNet model

vdabravolski/sagemaker-keras-mms

A sample project to show how to do inference of Keras models using Sagemaker Multi Model Server (MMS)

vdabravolski/Accelerate-Deep-Learning-Workloads-with-Amazon-SageMaker

Accelerate Deep Learning Workloads with Amazon SageMaker

vdabravolski/amazon-sagemaker-script-mode

Amazon SageMaker Script Mode examples

vdabravolski/aws-glue-samples

AWS Glue code samples

vdabravolski/aws-stepfunctions-byoc-mlops-using-data-science-sdk

Build Train and Deploy your own custom container using AWS StepFunctions Data Science SDK

vdabravolski/cw_lambda_publisher

Implementation of 2 Lambda functions: one to publish custom metric in CW & another to get custom metrics and calculate advanced statistics for scaling

vdabravolski/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.

vdabravolski/DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

vdabravolski/detectron2

Detectron2 is FAIR's next-generation platform for object detection and segmentation.

vdabravolski/distributed-train-and-deploy

vdabravolski/fastertransformer_backend

vdabravolski/gpt-neo

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

vdabravolski/kserve

Standardized Serverless ML Inference Platform on Kubernetes

vdabravolski/ml_immersion_day

to persist progress somewhere

vdabravolski/mmdetection

OpenMMLab Detection Toolbox and Benchmark

vdabravolski/pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

vdabravolski/sagemaker-custom-spark-container

vdabravolski/sagemaker-training-toolkit

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

vdabravolski/sklearn-anomaly-detection

Sample repo to do anomaly detection using Sagemaker Distributed Training

vdabravolski/transformers

🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

vdabravolski/transformers-inference-on-sagemaker

A sample repo to show how to optimize NLP inference on Amazon SageMaker

vdabravolski/transformers-sagemaker

Implementations of HuggingFace transformer framework to train and deploy on Amazon Sagemaker platform

vdabravolski/triton

Development repository for the Triton language and compiler