Jules S. Damji's repositories
ray-core-tutorial
Introduction to Ray Core Design Patterns and APIs.
mlflow-workshop-part-2
Partly lecture and partly a hands-on tutorial and workshop, this is a three part series on how to get started with MLflow. In this four part series, we will cover MLflow Tracking, Projects, Models, and Model Registry.
genai-cookbook
A mixture of Gen AI cookbook recipes for Gen AI applications.
tmls-workshop
Toronto Machine Learning MLflow Workshop
feast_workshops
A series of workshop modules introducing Feast feature store.
olt-mlflow
O'Reilly Online Training Materials for MLflow
ray-core-serve-tutorial-mlops
A two part tutorial for Ray Core APIs and Ray Serve for Model Deployment
mlflow-workshop-project-expamle-1
This example demonstrates how you can use GitHub projects in MLflow and share it with others to reproduce runs
LearningSparkV2
This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]
pycaret-demo-mlflow
pycaret-demo-mlflow
ray-misc-examples
All Things Ray!
academy
Ray tutorials from Anyscale
ad-serving-tutorial
Tecton's tutorial for using an Enterprise Feature Store.
cookbook
Jules Fork for PRs
data-assets
Assets for blogs, datasets, slides, notebooks etc
devAIWorld23
Tutorial for Ray Core Workshop for Dev AI World 2023
feast
Feature Store for Machine Learning
feast-fraud-tutorial
Resources backing the Feast fraud tutorial on GCP
koalas
Koalas: pandas API on Apache Spark
ray
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
ray-code-snippets
This is supplementary repo for creating and testing Ray API code examples
ray_tutorial
An introductory tutorial about leveraging Ray core features for distributed patterns.
spark
Apache Spark
tune-sklearn
A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.