Jul 2019
22 Mon
23 Tue
24 Wed
25 Thu 09:15 AM – 05:45 PM IST
26 Fri 09:20 AM – 05:30 PM IST
27 Sat
28 Sun
Jul 2019
22 Mon
23 Tue
24 Wed
25 Thu 09:15 AM – 05:45 PM IST
26 Fri 09:20 AM – 05:30 PM IST
27 Sat
28 Sun
Maulik Soneji
GoFood, the food delivery product of Gojek is one of the largest of its kind in the world. This talk summarizes the approaches considered and lessons learnt during the design and successful experimentation of a search system that uses ML to personalize the restaurant results based on the user’s food and taste preferences .
We formulated the estimation of the relevance as a Learning To Rank ML problem which makes the task of performing the ML inference for a very large number of customer-merchant pairs the next hurdle.
The talk will cover our learnings and findings for the following:
a. Creating a Learning Model for Food Recommendations
b. Targetting experiments to a certain percentage of users
c. Training the model from real time data
d. Enriching Restaurant data with custom tags
Our story should help the audience in making design decisions on the data pipelines and software architecture needed when using ML for relevance ranking in high throughput search systems.
No pre-requisite is required for the presentation.
Having knowledge about Elasticsearch and ML will help them grasp our use case better.
Maulik Soneji is currently working as a Data Engineer at Gojek where he works with different parts of data pipelines for a hyper-growth startup. Outside of learning about data systems, he is interested in elasticsearch, golang and kubernetes.
https://docs.google.com/presentation/d/1zUVFb0XvoVZ7ZHN6c-omQ6JxPLkn5osSLcDoCpD7PHk/edit?usp=sharing
Jul 2019
22 Mon
23 Tue
24 Wed
25 Thu 09:15 AM – 05:45 PM IST
26 Fri 09:20 AM – 05:30 PM IST
27 Sat
28 Sun
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