Скачать или смотреть Distributed ML Projects with Horovod and Spark

Data science is driving exciting changes and progress in computing. With the growing amount of data, new possibilities are opening up, and so is the continuously growing need for distributed machine learning systems. In several cases where the datasets are too large or complex, there is a natural advantage in opting for distributed ML systems as it enables getting better end results quickly. But what is it all about, and how can a data scientist go about it?

In this live session, we'll discuss distributed machine learning systems and dive deeper into their application with Horovod and Spark. Here's what we're covering as the learning outcomes for this particular session -

What are Horovod and Spark?
Write a simple algorithm on Spark
Why Horovod?
Horovod Vs. Apache Spark Vs. Pytorch Distributed in Production
Sample program
Summary

About the Speaker

Parth Sharma is a Chief Data Scientist at the Market Research giant Jasper Colin Research. He has experience in developing Distributed machine learning-based applications and System Design. Parth has trained over 2500+ Students in Topics like Data Science, Machine Learning, NLP, Deep Learning, Data Structures, and more. Parth proactively works with startups and has helped numerous startups and tech giants to help build Scalable and Reliable Applications and solutions. He is a passionate educator and loves coffee a lot!