Posts by Michael Galarnyk

Local Machine Cloud
12 . 15 . 2021

How to Speed Up XGBoost Model Training

XGBoost is an open-source implementation of gradient boosting designed for speed and performance. However, even XGBoost training can sometimes be slow. This post reviews some approaches for accelerating this process like changing tree construction me...

ray 1.9
12 . 06 . 2021

Ray version 1.9 has been released

Ray version 1.9 has been released! Release highlights include: Ray Train is now in beta, Ray Datasets now supports groupby and aggregations, Ray Docker images for multiple CUDA versions, improved Windows support, and a Ray Job Submission server.

11 . 16 . 2021

Considerations for Deploying Machine Learning Models in Production

A common grumble among data science or machine learning researchers or practitioners is that putting a model in production is difficult. As a result, some claim that a large percentage, 87%, of models never see the light of the day in production.


Ray 1.8
11 . 04 . 2021

Ray version 1.8 has been released

Ray version 1.8 has been released! Release highlights include: Ray SGD has been renamed to Ray Train, Ray Datasets is now in beta, and experimental support for Ray on Apple Silicon (M1 Macs)

Ray 1.7
10 . 11 . 2021

Ray version 1.7 has been released

Ray version 1.7 is here. Highlights include: Ray SGD v2 and is in alpha, Ray Workflows is in alpha, and major enhancements to the C++ API

Where Ray Serve Fits In
10 . 01 . 2021

Serving ML Models in Production: Common Patterns

Over the past couple years, we've listened to ML practitioners across many different industries to learn and improve the tooling around ML production use cases. Through this, we've seen 4 common patterns of machine learning in production: pipeline, e...

With and without NumPy Ray
09 . 02 . 2021

Parallelizing Python Code

This article reviews some common options for parallelizing Python code including process-based parallelism, specialized libraries, ipython parallel, and Ray.

Introduction to Reinforcement Learning
08 . 26 . 2021

An Introduction to Reinforcement Learning with OpenAI Gym, RLlib, and Google Colab

An introductory tutorial on reinforcement learning with OpenAI Gym, RLlib, and Google Colab.

08 . 24 . 2021

Fast AutoML with FLAML + Ray Tune

FLAML is a lightweight Python library from Microsoft Research that finds accurate machine learning models in an efficient and economical way using cutting edge algorithms designed to be resource-efficient and easily parallelizable. FLAML can also uti...

Ray Dashboard 8 Core
08 . 12 . 2021

Writing your First Distributed Python Application with Ray

Ray is a fast, simple distributed execution framework that makes it easy to scale your applications and to leverage state of the art machine learning libraries. Using Ray, you can take Python code that runs sequentially and transform it into a distri...