London Meetup: Deep Dive into TensorFlow #24

Date: 
Wednesday, June 19, 2019 - 17:30
Source: 
TensorFlow
Attendees: 
89
City: 
London

Welcome to TensorFlow London Meetup #24!

This event is hosted in collaboration with Google team and will be held at Google London, Belgrave House (level 5).

REGISTER HERE! https://www.eventbrite.com/e/london-meetup-deep-dive-into-tensorflow-24-tickets-63173470551

AGENDA:
5:30 - Doors open. Networking. Drinks & Pizza
6:00 - Opening remarks
6:10 - 6:25 - Lightning Talk
6.35 - 7:00 - Going packaging free with ML on Google Cloud Platform by Alexandra Abbas, Data Scientist at Datatonic
7:00 - 7:25 - TensorFlow Extended (TFX), an end-to-end platform for deploying production ML pipelines by Christos Aniftos, ML specialist at Google Cloud
7:25 - 7:50 - Overview of TensorFlow.js by Nikos Katsikanis, Director at QuantumJS
8:00 - 8:15 - Q&A

TALK DETAILS:

Speaker: Alexandra Abbas, Data Scientist at Datatonic
Title: Going packaging free with ML on Google Cloud Platform

Talk details:
In their bid to become packaging-free, a global Cosmetics Retailer is developing a mobile app allowing customers to view product information simply by taking a picture. This completely eliminates the need for packaging and labels. However, in order to do this effectively, they needed an accurate Image Classification model available both on Android and iOS. To help them achieve their goal, Alexandra and her colleagues developed a mobile-friendly Image Classification model and an end-to-end, fully automated model training and serving pipeline orchestrated with Google Cloud Composer. This framework enables to re-train the model on Google AI Platform as new data land on Cloud Storage, monitor the new model performance in a BigQuery evaluation table and access the newly created TFLite model on a serving bucket. Alexandra explains how to productionize your Machine Learning pipeline using serverless and managed technologies and what challenges to count on when bringing your model to mobile, through an exciting real-life case study.

Bio: Alexandra is a Data Scientist at Datatonic working on large-scale innovation projects in Data Engineering and Machine Learning, she spends most of her time creating data pipelines using Big Data technologies like Apache Beam and Airflow and building production ready ML models using Tensorflow. Alexandra is a curious mind who enjoys problem-solving and exploring new technologies. She is an initiator of and passionate about the productionisation of Machine Learning models. Twitter @alexandraabbas

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Speaker: Christos Aniftos, ML specialist at Google Cloud (details coming soon)

Title: TensorFlow Extended (TFX), an end-to-end platform for deploying production ML pipelines

Talk details: When you’re ready to go beyond training a single model, or ready to put your amazing model to work and move it to production, TFX is there to help you build a complete ML pipeline.

A TFX pipeline is a sequence of components that implement an ML pipeline which is specifically designed for scalable, high-performance machine learning tasks. That includes modeling, training, serving inference, and managing deployments to online, native mobile, and JavaScript targets.

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Speaker: Nikos Katsikanis, Director at Quantum JS
Title: Overview of TensorFlow.js

Talk details: An overview of the library and what the community is doing. A quick example running Convolution Image analysis will be given too.

Bio: Nikos is a Science (STEM) graduate and has over twelve years of professional software development experience in a wide variety of teams and technical stacks. Through the years he has cultivated many relationships with appropriate technical experts who can be utilised for tech business and/or startup. He has also trained many software developers and has seen how quickly junior developers can enhance value and accrue productivity.

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