Workshop: Tensorflow: Building Neural Machine Translation

Location:

Level: 
Intermediate

When:

1:00pm - 4:00pm

Key takeaways

  • What is Tensorflow?
  • How to use it?
  • What are neural networks?
  • How to use neural networks to translate languages using Tensorflow?

Prerequisites

  1. You should bring you laptop with Tensorflow installed
  2. Have a python IDE installed. I prefer version 2016.3
  3. Install Anaconda Navigator. This will help you install certain basic packages like Numpy, Pandas, Keras, etc.
  4. Additional instructions will be updated on 1 Nov 2017 in my Github repository QCon_Nov2017.

With global commerce on the rise, collaboration between individuals speaking different languages is essential. The need for real time and accurate Language translation using deep networks is picking up fast.

Historically, language translation was done using rules and examples. This is obviously not scalable and does not cater to the evolution of languages. Later word-based and phrase-based translations were invented that still could not address the need of the hour. The modern day translations are done using deep networks. I would like to discuss the topic of language translation and deep learning using Tensorflow.

The attendees will get a chance to work hands-on to create the building blocks of Language Translator using Tensorflow.

Agenda:

  • Intro to Tensorflow
  • Intro to neural networks
  • LSTM, Language Corpus, BLEU scores
  • Sequence to sequence models
  • Encoders and Decoders
  • Attention
  • Connect a Language Model (LM) with NMT
  • Multi language translator
  • Bidirectional encoder
  • Data augmentation

Speaker: Karunakar Singamreddy

ML/NLP Tech startup CEO & founder @Pamoru

SK is a AI and ML expert and a successful twice start-up entrepreneur. He is a frequent speaker in meetups and a ML/NLP blogger. He believes that machine learning and NLP enthusiasts are looking for ML/NLP sessions where they can understand more of 'how' rather than 'what'.

His focus is to develop ML models to combine image and text processing. Also he has developed solutions in text summarization, question-answering and text mining.

Find Karunakar Singamreddy at

Other Workshops:

.

Tracks

  • Architectures You've Always Wondered About

    Architectural practices from the world's most well-known properties, featuring startups, massive scale, evolving architectures, and software tools used by nearly all of us.

  • Going Serverless

    Learn about the state of Serverless & how to successfully leverage it! Lessons learned in the track hit on security, scalability, IoT, and offer warnings to watch out for.

  • Microservices: Patterns and Practices

    Stories of success and failure building modern Microservices, including event sourcing, reactive, decomposition, & more.

  • DevOps: You Build It, You Run It

    Pushing DevOps beyond adoption into cultural change. Hear about designing resilience, managing alerting, CI/CD lessons, & security. Features lessons from open source, Linkedin, Netflix, Financial Times, & more. 

  • The Art of Chaos Engineering

    Failure is going to happen - Are you ready? Chaos engineering is an emerging discipline - What is the state of the art?

  • The Whole Engineer

    Success as an engineer is more than writing code. Hear inward looking thoughts on inclusion, attitude, leadership, remote working, and not becoming the brilliant jerk.

  • Evolving Java

    Java continues to evolve & change. Track covers Spring 5, async, Kotlin, serverless, the 6-month cadence plans, & AI/ML use cases.

  • Security: Attacking and Defending

    Offense and defensive security evolution that application developers should know about including SGX Enclaves, effects of AI, software exploitation techniques, & crowd defense

  • The Practice & Frontiers of AI

    Learn about machine learning in practice and on the horizon. Learn about ML at Quora, Uber's Michelangelo, ML workflow with Netflix Meson and topics on Bots, Conversational interfaces, automation, and deployment practices in the space.

  • 21st Century Languages

    Compile to Native, Microservices, Machine learning... tailor-made languages solving modern challenges, featuring use cases around Go, Rust, C#, and Elm.

  • Modern CS in the Real World

    Applied trends in Computer Science that are likely to affect Software Engineers today. Topics include category theory, crypto, CRDT's, logic-based automated reasoning, and more.

  • Stream Processing In The Modern Age

    Compelling applications of stream processing using Flink, Beam, Spark, Strymon & recent advances in the field, including Custom Windowing, Stateful Streaming, SQL over Streams.