Machine Learning GDEs:

Alicja Heisig
Google Developer Experts
5 min readApr 9, 2021

Q1 2021 highlights, projects and achievements

Written by HyeJung Lee and MJ You, Google ML Ecosystem Community Managers. Reviewed by Soonson Kwon, Developer Relations Program Manager.

Google Developers Experts is a community of passionate developers who love to share their knowledge with others. Many of them specialize in Machine Learning (ML). Despite many unexpected changes over the last months and reduced opportunities for various in person activities during the ongoing pandemic, their enthusiasm did not stop.

Here are some highlights of the ML GDE’s hard work during the Q1 2021 which contributed to the global ML ecosystem.

ML GDE YouTube channel

The brand new ML GDEs YouTube channel

With the initiative and lead of US-based GDE Margaret Maynard-Reid, we launched the ML GDEs YouTube channel. It is a great way for GDEs to reach global audiences, collaborate as a community, create unique content and promote each other’s work. The channel will contain materials covering a range of different topics, from tech talks, tutorials, workshops to interviews with members of the ML community. We are constantly working on adding new content to the channel, but many videos are already available to watch, including: ML GDE’s intro from all over the world, tips for TensorFlow & GCP Certification and how to use Google Cloud Platform. Subscribe to the channel now!!

TensorFlow Everywhere

17 ML GDEs presented at TensorFlow Everywhere (a global community-led event series for TensorFlow and Machine Learning enthusiasts and developers around the world) hosted by local TensorFlow user groups. You can watch the recorded sessions in the TensorFlow Everywhere playlist on the ML GDE Youtube channel. Most of the sessions cover new features in Tensorflow.

International Women’s Day

Many ML GDEs participated in activities to celebrate International Women’s Day (March 8th). GDE Ruqiya Bin Safi (based in Saudi Arabia) cooperated with WTM Saudi Arabia to organize “Socialthon” — social development hackathons and gave a talk “Successful Experiences in Social Development”, which reached 77K viewers live and hit 10K replays. India-based GDE Charmi Chokshi participated in GirlScript’s International Women’s Day event and gave a talk: “Women In Tech and How we can help the underrepresented in the challenging world”. If you’re looking for more inspiring materials, check out the “Women in AI” playlist on our ML GDE YouTube channel!

Mentoring

ML GDEs are also very active in mentoring community developers, students in the Google Developer Student Clubs and startups in the Google for Startups Accelerator program. Among many, GDE Arnaldo Gualberto (Brazil) conducted mentorship sessions for startups in the Google Fast Track program, discussing how to solve challenges using Machine Learning/Deep Learning with TensorFlow.

TensorFlow

A screenshot from “Practical Adversarial Robustness in Deep Learning: Problems and Solutions”.

Our GDEs from India, Sayak Paul and Dipanjan Sarkar along with Pin-Yu Chen (from IBM Research) created a tutorial “Practical Adversarial Robustness in Deep Learning: Problems and Solutions” which has been accepted at CVPR 2021. CVPR is a leading conference in the domain of Computer Vision. They collated theory and practice with TensorFlow code examples so that both academics and industry practitioners can benefit from this tutorial.

Recent publications of ML GDEs

Meanwhile in Europe, GDEs Alexia Audevart (based in France) and Luca Massaron (based in Italy) released “Machine Learning using TensorFlow Cookbook”. It provides simple and effective ideas to successfully use TensorFlow 2.x in computer vision, NLP and tabular data projects. Additionally, Luca published the second edition of the Machine Learning For Dummies book, first published in 2015. His latest edition is enhanced with product updates and the principal is a larger share of pages devoted to discussion of Deep Learning and TensorFlow / Keras usage.

Screenshot from the “Welcome to Deep Learning Course and Orientation” workshop

On top of her women-in-tech related activities, Ruqiya Bin Safi is also running a “Welcome to Deep Learning Course and Orientation” monthly workshop throughout 2021. The course aims to help participants gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow.

Screenshot of the “TensorFlow Project Showcase: Cash Recognition for Visually Impaired”

Nepal-based GDE Kshitiz Rimal gave a talk “TensorFlow Project Showcase: Cash Recognition for Visually Impaired” on his project which uses TensorFlow, Google Cloud AutoML and edge computing technologies to create a solution for the visually impaired community in Nepal.

Screenshot of the “Machine Learning-powered Pipelines to Augment Human Specialists”

On the other side of the world, in Canada, GDE Tanmay Bakshi presented a talk “Machine Learning-powered Pipelines to Augment Human Specialists” during TensorFlow Everywhere NA. It covered the world of NLP through Deep Learning, how it’s historically been done, the Transformer revolution, and how using the TensorFlow & Keras to implement use cases ranging from small-scale name generation to large-scale Amazon review quality ranking.

Google Cloud Platform

Artificial Intelligence on Google Cloud Platform” series

We have been equally busy on the GCP side as well. In the US, GDE Srivatsan Srinivasan created a series of videos called “Artificial Intelligence on Google Cloud Platform”, with one of the episodes, “Google Cloud Products and Professional Machine Learning Engineer Certification Deep Dive”, getting over 3,000 views.

“Machine Learning Pipeline (CI/CD for ML Products in GCP)” analysis

Korean GDE Chansung Park contributed to TensorFlow User Group Korea with his “Machine Learning Pipeline (CI/CD for ML Products in GCP)” analysis, focused on about machine learning pipeline in Google Cloud Platform.

Screenshot from the article “Seven Tips for Forecasting Cloud Costs”

Last but not least, GDE Gad Benram based in Israel wrote an article on “Seven Tips for Forecasting Cloud Costs”, where he explains how to build and deploy ML models for time series forecasting with Google Cloud Run. It is linked with his solution of building a cloud-spend control system that helps users more-easily analyze their cloud costs.

If you want to know more about the Google Experts community and all their global open-source ML contributions, visit the GDE Directory and connect with GDEs on Twitter and LinkedIn. You can also meet them virtually on the ML GDE’s YouTube Channel!

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Alicja Heisig
Google Developer Experts

Developer Relations Program Manager @Google. Foodie, sommelier, world traveler. Passionate about technology.