Leela Krishna Kandrakota

25 Abonné

Solutions Architect My current focus is Architecture for very large Distributed ML Systems and Data solutions using noSQL, newSQL, Streaming and Deep Learning . I like to keep an adaptive mindset to upcoming technologies and new algorithms. Quoting Eric Brewer - "There are many databases on this planet where the *data* outlasts any particular implementation, not only upgrading all hardware, backup systems and data centers but also changing software layers underneath. *Data* still persists across all this transitions! That was not easy to do but has been done many many times! " Strengths: • Motivated, Self-starter and natural Leader • Critical and Savvy problem-solver • Techn..

architecture enterprise data science ml

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Leela Krishna Kandrakota

Présentations

Well architected ML platforms for Enterprise Data Science

J’aime

Apache Flink 101 - the rise of stream processing and beyond

Mammalian Brain Chemistry Explains Everything

How Google Works

Implementing Effective Data Governance

An introduction to fundamental architecture concepts

Patterns of Streaming Applications

Analysing streaming data in real time (AWS)

Aljoscha Krettek - Portable stateful big data processing in Apache Beam

Yoga Vashishtha of Valmiki - Introduction

The YOGA of NUTRITION

Introduction to Srimad Bhagavatam

Design Thinking - Bootcamp

The role of Design Thinking

Advanced data modeling with apache cassandra

AWS Storage and Database Architecture Best Practices (DAT203) | AWS re:Invent 2013

The things we don't see – stories of Software, Scala and Akka

Premier Inside-Out: Apache Druid

Ensuring Kubernetes Cost Efficiency across (many) Clusters - DevOps Gathering 2019

Designing Cloud Native Applications with Kubernetes

Cloud-Native Application and Kubernetes

Pentesting GraphQL Applications

How to Productionize Your Machine Learning Models Using Apache Spark MLlib 2.x with Richard Garris

PyData Berlin 2018: dvc.org

Microservices in Clojure

Be A Great Product Leader (Amplify, Oct 2019)

A few thoughts on work life-balance

Transaction Management on Cassandra

Introducing Domain Driven Design - codemash

Managing the Complete Machine Learning Lifecycle with MLflow

MLOps Virtual Event | Building Machine Learning Platforms for the Full Lifecycle