Pinned Repositories
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's Repositories
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