This document discusses using Docker for machine learning and natural language processing projects. It introduces Spago, an open source machine learning library written in Go, and demos deploying a Spago project to Kubernetes using Okteto. The key points are: - Docker is useful for ML development as it allows packaging models and code into containers for scalable and reproducible deployments. - Spago is a pure Go library for NLP tasks like named entity recognition and question answering that aims to optimize CPU usage. - Okteto allows easily deploying Docker Compose stacks to Kubernetes with minimal configuration. - A live demo then shows deploying a Spago project to Kubernetes with Okteto.

1. Spago Self ConTained
ML & NLP Library & Deploy on Okteto

2. Agenda
For all level Audience ( Docker Knowledge + point )
Docker for Golang Developer
ML + NLP
Why Docker + ML
Live Demo !
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3. “
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Sangam Biradar
Docker Community Leader
Cloud Native Developer .
Github: Sangam14
Join Community http://discord.kubedaily.live/

5. Why Docker + ML?
Docker is Not just in ML but across the entire development phase

6. What you should & shouldn’t include
in ML Development Container
⩥ Only the ML frameworks & Dependencies
⩥ ML frameworks and Dependencies & training
code ( scaling workload on cluster )
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Spago
A Machine Learning Library Written in Pure Go
Designed to support Neural Architectures in NLP

8. - educational purpose
- production use
- High Quality Implementation
Purpose of spago
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9. Where would I use SpaGo ?
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⩥ Production NLP system
⩥ Required Optimization of
CPU interference
⩥ Relies on GONUM assembly
code with SIMD instruction
⩥ CGO is bottleneck , so there
are experiment with intel
MKL, Apache Arrow
⩥ Also experiment with sparse
model , LSH , etc
⩥ Training of No-very-deep model
⩥ The training seems less
interesting as its expensive for
modern model even with
GPUS/TPUs

10. Ready to use
⩥ Compatible with pytorch model
⩥ Transformer 50+ pretrained model in 100+ langauges
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11. Use for “production level ml/nlp”
⩥ Train shallow models
⩥ fine tune deep model
⩥ inference
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⩥ Train deep model
⩥ fine tune deep model
⩥ inference
Weight importer

12. Real time examples
⩥ Named Entities Recognition
⩥ Hugging Face Importer
⩥ Question Answering
⩥ Masked Language Model
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13. Okteto – Kubernetes Developer platform
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15. Docker Compose on kubernetes
⩥ okteto stack is easy way to deploy your docker
compose within secs .
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Image name (eg. any image from
docker hub
name of your stack
build context
Override default
entry point
Port exposed by
each service
Resource quota
volume

17. Demo Time !!
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18. Connect with me !
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