srikanth-datascientist Goto Github PK

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amazon-sagemaker-examples

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

awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

churn

course-ds-base

course-ds-base

dataengineering

⭕️ Data Engineering for Data Scientists

explainable-ai-workshop

fourthbrain

This is a collection of live coding exercises, homework assignments and the like created during my experience with Fourth Brain

fsdl-text-recognizer-2021-labs

Complete deep learning project developed in Full Stack Deep Learning, Spring 2021

huggingface

machine-learning-engineering-for-production-public

Public repo for DeepLearning.AI MLEP Specialization

madewithml

Learn how to responsibly deliver value with ML.

mlops

A project-based course on the foundations of MLOps with a focus on intuition and application.

mlops-basics

The goal of the series is to understand the basics of MLOps (model building, monitoring, configurations, testing, packaging, deployment, cicd)

mlops-zoomcamp

Free MLOps course from DataTalks.Club

mlops_end2end

mlprojecttemplate

Cookie cutter template for Machine Learning Project

srigit

srikanth-datascientist

Config files for my GitHub profile.

srimlops

Repo to learn MLOps Basics

tensorflowrt

Hands on Project on Optimize TensorFlow models fro deployment with TensorFlowRT

training-data-analyst

Labs and demos for courses for GCP Training (http://cloud.google.com/training).

vertexpipelines

Pipelines help you automate and reproduce your ML workflow. Vertex AI integrates the ML offerings across Google Cloud into a smooth development experience. Previously, models trained with AutoML and custom models were accessible via separate services. Vertex AI combines both into a single API, along with other new products. Vertex AI also includes a variety of MLOps products, like Vertex Pipelines.