yapweiyih

amazon-sagemaker-entrypoint-utilities

Sample utilities to shorten or simplify Amazon SageMaker's training entrypoint: logging handlers, silenced tqdm, hyperparameter parsings, etc.

amazon-sagemaker-gluonts-entrypoint

Sample GluonTS entrypoint scripts for Amazon SageMaker.

amazon-textract-serverless-large-scale-document-processing

Process documents at scale using Amazon Textract

rl-testbed-for-energyplus

Reinforcement Learning Testbed for Power Consumption Optimization using EnergyPlus

sagemaker-custom-training-containers

Implementations of Amazon SageMaker-compatible custom containers for training.

yapweiyih/amazon-sagemaker-entrypoint-utilities

Sample utilities to shorten or simplify Amazon SageMaker's training entrypoint: logging handlers, silenced tqdm, hyperparameter parsings, etc.

yapweiyih/amazon-sagemaker-gluonts-entrypoint

Sample GluonTS entrypoint scripts for Amazon SageMaker.

yapweiyih/rl-testbed-for-energyplus

Reinforcement Learning Testbed for Power Consumption Optimization using EnergyPlus

yapweiyih/sagemaker-custom-training-containers

Implementations of Amazon SageMaker-compatible custom containers for training.

yapweiyih/amazon-textract-serverless-large-scale-document-processing

Process documents at scale using Amazon Textract

yapweiyih/aws-cloudformation-templates

A collection of useful CloudFormation templates

yapweiyih/blogpost

yapweiyih/code-sharing

yapweiyih/deepspeed-on-aws

yapweiyih/diaglogflow-practise

yapweiyih/djl-serving

A universal scalable machine learning model deployment solution

yapweiyih/ForecastPOC

A collection of notebooks and resources to operate an Amazon Forecast POC in a box.

yapweiyih/iSpindel

electronic Hydrometer

yapweiyih/jupyter_environment_kernels

An Jupyter plugin to enable the automatic detection of conda and virtualenv environments as kernels.

yapweiyih/linuxcfg

My Linux configurations

yapweiyih/mlmax

Example templates for the delivery of custom ML solutions to production so you can get started quickly without having to make too many design choices.

yapweiyih/nn

🧠 Minimal implementations/tutorials of deep learning papers with side-by-side notes; including transformers (original, xl, switch, feedback), optimizers(adam, radam, adabelief), gans(dcgan, cyclegan), reinforcement learning (ppo, dqn), capsnet, sketch-rnn, etc.

yapweiyih/Open_Data_QnA

The Open Data QnA python library enables you to chat with your databases by leveraging LLM Agents on Google Cloud. Open Data QnA enables a conversational approach to interacting with your data.

yapweiyih/PersonalizePOC

POC In a box guide material for Amazon Personalize

yapweiyih/python-project-skeleton

A simple project structure for Python

yapweiyih/pytorch-widedeep

A flexible package to combine tabular data with text and images using Wide and Deep models in Pytorch

yapweiyih/pyutil

Collections of code fragments

yapweiyih/reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction

yapweiyih/reStructuredText-Documentation-Reference

Tutorial and reference for reStructuredText documentation.

yapweiyih/smallmatter-package

Sample wrappers to streamline data-science tasks using Python toolkits (such as pandas, matplotlib, etc.) on AWS.

yapweiyih/smworkshop

yapweiyih/template-doc

yapweiyih/ts-crash-course

yapweiyih/uc-job-search-deployment