tselmeg-c Goto Github PK

ai-platform-samples

Official Repo for Google Cloud AI Platform

aipnd

Code and associated files for the AI Programming with Python Nanodegree Program

airflow

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

amazon-dsstne

Deep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models

churn_prediction_udacity_capstone

Solved churn prediction problem on an event data set and exemplified big data handling skills with Spark on AWS

course-collaboration-travel-plans

deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

dsnd_term2

Contains files related to content and project of DSND Term 2

feast_feature_store

findfib

gcp-kfp-tutorial

lighthouse

Automated auditing, performance metrics, and best practices for the web.

llama_index

LlamaIndex (formerly GPT Index) is a data framework for your LLM applications

machine-learning

Content for Udacity's Machine Learning curriculum

merlin

NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.

model-interpretability

Interpret ANY machine learning model

models

Merlin Models is a collection of deep learning recommender system model reference implementations

my-travel-plans

Udacity_GitHub Course Practice

nd027-c3-data-lakes-with-spark

nd064_course_1

nvidia-merlin-on-vertex-ai

This repository compiles prescriptive guidance and code samples for the operationalization of NVIDIA Merlin framework on Google Cloud Vertex AI.

plan.net

recmetrics

A library of metrics for evaluating recommender systems

scalecast-examples

Examples of the application of individual scalecast models

surprise

A Python scikit for building and analyzing recommender systems

systems

Merlin Systems provides tools for combining recommendation models with other elements of production recommender systems (like feature stores, nearest neighbor search, and exploration strategies) into end-to-end recommendation pipelines that can be served with Triton Inference Server.

tc-learn-docker

docker CI/CD exercise repo

test

time-series-forecasting

Time series forecasting of some Indian Restaurant

training-data-analyst

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