South African developers build web application to help local athletes

Posted by Aniedi Udo-Obong, Sub-Saharan Africa Regional Lead, Google Developer Groups

Lesego Ndlovu and Simon Mokgotlhoa have stayed friends since they were eight years old, trading GameBoy cartridges and playing soccer. They live three houses away from each other in Soweto, the biggest township in South Africa, with over one million residents. The two friends have always been fascinated by technology, and by the time the duo attended university, they wanted to start a business together that would also help their community.

Lesego Ndlovu and Simon Mokgotlhoa sitting at a desk on their computers

After teaching themselves to code and attending Google Developer Groups (GDG) events in Johannesburg, they built a prototype and launched a chapter of their own (GDG Soweto) to teach other new developers how to code and build technology careers.

Building an app to help their community

Lesego and Simon wanted to build an application that would help the talented soccer players in their community get discovered and recruited by professional soccer teams. To do that, they had to learn to code.

Lesego Ndlovu and Simon Mokgotlhoa holding their phones towards the screen showcasing the Ball Talent app

“We always played soccer, and we saw talented players not get discovered, so, given our interest in sports and passion for technology, we wanted to make something that could change that narrative,” Lesego says. “We watched videos on the Chrome Developers YouTube channel and learned HTML, CSS, and JavaScript, but we didn’t know how to make an app, deliver a product, or start a business. Our tech journey became a business journey. We learned about the code as the business grew. It’s been a great journey.”

After many all-nighters learning frontend development using HTML, CSS, and JavaScript, and working on their project, they built BallTalent, a Progressive Web App (PWA), that helps local soccer players in their neighborhood get discovered by professional soccer clubs. They record games in their neighborhood and upload them to the app, so clubs can identify new talent.

“We tested our prototype with people, and it seemed like they really loved it, which pushed us to keep coding and improving on the project,” says Simon. “The application is currently focused on soccer, but it’s built it in a way that it can focus on other sports.”

In 2019, when BallTalent launched, the project placed in the top 5 of one of South Africa’s most prestigious competitions, Diageo Social Tech Startup Challenge. BallTalent has helped local soccer players match with professional teams, benefiting the community. Simon and Lesego plan to release version two soon, with a goal of expanding to other sports.

Learning to code with web technologies and resources

Lesego and Simon chose to watch the Chrome Developers YouTube channel to learn to code, because it was free, accessible, and taught programming in ways that were easy to understand. Preferring to continue to use free Google tools because of their availability and ease of use, Lesego and Simon used Google developer tools on Chrome to build and test the BallTalent app, which is hosted on Google Cloud Platform.

BallTalent Shows Youth Talent to the Worlds Best Scouts and Clubs

They used NodeJS as their backend runtime environment to stay within the Google ecosystem–NodeJS is powered by the V8 JavaScript engine, which is developed by the Chromium Project. They used a service worker codelab from Google to allow users to install the BallTalent PWA and see partial content, even without an internet connection.

We are focused on HTML, CSS, JavaScript, frontend frameworks like Angular, and Cloud tools like Firebase, to be able to equip people with the knowledge of how to set up an application,” says Simon.

Moving gif of soccer players playing on a soccer field

BallTalent shares sample footage of a previous match: Mangaung United Vs Bizana Pondo Chiefs, during the ABC Motsepe Play Offs

“Google has been with us the whole way,” says Simon.

Contributing to the Google Developer community

Because of their enthusiasm for web technologies and positive experience learning to code using Google tools, Lesego and Simon were enthusiastic about joining a Google Developer Community. They became regular members at GDG Johannesburg and went to DevFest South Africa in 2018, where they got inspired to start their own GDG chapter in Soweto. The chapter focuses on frontend development to meet the needs of a largely beginner developer membership and has grown to 500+ members.

Looking forward to continued growth

The duo is now preparing to launch the second version of their BallTalent app, which gives back to their community by pairing local soccer talent with professional teams seeking players. In addition, they’re teaching new developers in their township how to build their own apps, building community and creating opportunities for new developers. Google Developer Groups are local community groups for developers interested in learning new skills, teaching others, and connecting with other developers. We encourage you to join us, and if you’re interested in becoming a GDG organizer like Simon and Lesego, we encourage you to apply.

Experts.Anyone.Anywhere

Posted by Janelle Kuhlman, Developer Relations Program Manager

Click above to meet our community of Experts

The Google Developer Experts program is a global network of highly experienced technology experts, developers and thought leaders. GDEs share their expertise with other developers and tech communities through a variety of ways such as speaking engagements, mentorship and content writing. The community has access to an exclusive network of experts that span across different Google technologies including Android, Cloud, Machine Learning and more.

Get to know our diverse community and subscribe to the Google Developers YouTube Channel to stay informed on the latest updates across our products and platforms!

Finding courage and inspiration in the developer community

Posted by Monika Janota

How do we empower women in tech and equip them with the skills to help them become true leaders? One way is learning from others’ successes and failures. Web GDEs—Debbie O’Brien, Julia Miocene, and Glafira Zhur—discuss the value of one to one mentoring and the impact it has made on their own professional and personal development.

A 2019 study showed that only 25% of keynote speakers at tech events are women, meanwhile 70% of female speakers mentioned being the only woman on a conference panel. One way of changing that is by running programs and workshops with the aim of empowering women and providing them with the relevant soft skills training, including public speaking, content creation, and leadership. Among such programs are the Women Developer Academy (WDA) and the Road to GDE, both run by Google’s developer communities.

With more than 1000 graduates around the world, WDA is a program run by Women Techmakers for professional IT practitioners. To equip women in tech with speaking and presentation skills, along with confidence and courage, training sessions, workshops, and mentoring meetings are organized. Road to GDE, on the other hand, is a three-month mentoring program created to support people from historically underrepresented groups in tech on their path to becoming experts. What makes both programs special is the fact that they’re based on a unique connection between mentor and mentee, direct knowledge sharing, and an individualized approach.

Photo of Julia Miocene speaking at a conference Julia Miocene

Some Web GDE community members have had a chance to be part of the mentoring programs for women as both mentors and mentees. Frontend developers Julia Miocene and Glafira Zhur are relatively new to the GDE program. They became Google Developers Experts in October 2021 and January 2022 respectively, after graduating from the first edition of both the Women Developer Academy and the Road to GDE; whilst Debbie O’Brien has been a member of the community and an active mentor for both programs for several years. They have all shared their experiences with the programs in order to encourage other women in tech to believe in themselves, take a chance, and to become true leaders.

Different paths, one goal

Although all three share an interest in frontend development, each has followed a very different path. Glafira Zhur, now a team leader with 12 years of professional experience, originally planned to become a musician, but decided to follow her other passion instead. A technology fan thanks to her father, she was able to reinstall Windows at the age of 11. Julia Miocene, after more than ten years in product design, was really passionate about CSS. She became a GDE because she wanted to work with Chrome and DevTools. Debbie is a Developer Advocate working in the frontend area, with a strong passion for user experience and performance. For her, mentoring is a way of giving back to the community, helping other people achieve their dreams, and become the programmers they want to be. At one point while learning JavaScript, she was so discouraged she wanted to give it up, but her mentor convinced her she could be successful. Now she’s returning the favor.

Photo of Debbie O'Brien and another woman in a room smiling at the camera

Debbie O’Brien

As GDEs, Debbie, Glafira, and Julia all mention that the most valuable part of becoming experts is the chance to meet people with similar interests in technology, to network, and to provide early feedback for the web team. Mentoring, on the other hand, enables them to create, it boosts their confidence and empowers them to share their skills and knowledge—regardless of whether they’re a mentor or a mentee.

Sharing knowledge

A huge part of being a mentee in Google’s programs is learning how to share knowledge with other developers and help them in the most effective way. Many WDA and Road to GDE participants become mentors themselves. According to Julia, it’s important to remember that a mentor is not a teacher—they are much more. The aim of mentoring, she says, is to create something together, whether it’s an idea, a lasting connection, a piece of knowledge, or a plan for the future.

Glafira mentioned that she learned to perceive social media in a new way—as a hub for sharing knowledge, no matter how small the piece of advice might seem. It’s because, she says, even the shortest Tweet may help someone who’s stuck on a technical issue that they might not be able to resolve without such content being available online. Every piece of knowledge is valuable. Glafira adds that, “Social media is now my tool, I can use it to inspire people, invite them to join the activities I organize. It’s not only about sharing rough knowledge, but also my energy.”

Working with mentors who have successfully built an audience for their own channels allows the participants to learn more about the technical aspects of content creation—how to choose topics that might be interesting for readers, set up the lighting in the studio, or prepare an engaging conference speech.

Learning while teaching

From the other side of the mentor—mentee relationship, Debbie O’Brien says the best thing about mentoring is seeing the mentees grow and succeed: “We see in them something they can’t see in themselves, we believe in them, and help guide them to achieve their goals. The funny thing is that sometimes the advice we give them is also useful for ourselves, so as mentors we end up learning a lot from the experience too.”

TV screenin a room showing and image od Glafira Zhur

Glafira Zhur

Both Glafira and Julia state that they’re willing to mentor other women on their way to success. Asked what is the most important learning from a mentorship program, they mention confidence—believing in yourself is something they want for every female developer out there.

Growing as a part of the community

Both Glafira and Julia mentioned that during the programs they met many inspiring people from their local developer communities. Being able to ask others for help, share insights and doubts, and get feedback was a valuable lesson for both women.

Mentors may become role models for the programs’ participants. Julia mentioned how important it was for her to see someone else succeed and follow in their footsteps, to map out exactly where you want to be professionally, and how you can get there. This means learning not just from someone else’s failures, but also from their victories and achievements.

Networking within the developer community is also a great opportunity to grow your audience by visiting other contributors’ podcasts and YouTube channels. Glafira recalls that during the Academy, she received multiple invites and had an opportunity to share her knowledge on different channels.

Overall, what’s even more important than growing your audience is finding your own voice. As Debbie states: “We need more women speaking at conferences, sharing knowledge online, and being part of the community. So I encourage you all to be brave and follow your dreams. I believe in you, so now it’s time to start believing in yourself.”

Machine Learning Communities: Q1 ‘22 highlights and achievements

Posted by Nari Yoon, Hee Jung, DevRel Community Manager / Soonson Kwon, DevRel Program Manager

Let’s explore highlights and accomplishments of vast Google Machine Learning communities over the first quarter of the year! We are enthusiastic and grateful about all the activities that the communities across the globe do. Here are the highlights!

ML Ecosystem Campaign Highlights

ML Olympiad is an associated Kaggle Community Competitions hosted by Machine Learning Google Developers Experts (ML GDEs) or TensorFlow User Groups (TFUGs) sponsored by Google. The first round was hosted from January to March, suggesting solving critical problems of our time. Competition highlights include Autism Prediction Challenge, Arabic_Poems, Hausa Sentiment Analysis, Quality Education, Good Health and Well Being. Thank you TFUG Saudi, New York, Guatemala, São Paulo, Pune, Mysuru, Chennai, Bauchi, Casablanca, Agadir, Ibadan, Abidjan, Malaysia and ML GDE Ruqiya Bin Safi, Vinicius Fernandes Caridá, Yogesh Kulkarni, Mohammed buallay, Sayed Ali Alkamel, Yannick Serge Obam, Elyes Manai, Thierno Ibrahima DIOP, Poo Kuan Hoong for hosting ML Olympiad!

Highlights and Achievements of ML Communities

TFUG organizer Ali Mustufa Shaikh (TFUG Mumbai) and Rishit Dagli won the TensorFlow Community Spotlight award (paper and code). This project was supported by provided Google Cloud credit.

ML GDE Sachin Kumar (Qatar) posted Build a retail virtual agent from scratch with Dialogflow CX – Ultimate Chatbot Tutorials. In this tutorial, you will learn how to build a chatbot and voice bot from scratch using Dialogflow CX, a Conversational AI Platform (CAIP) for building conversational UIs.

ML GDE Ngoc Ba (Vietnam) posted MTet: Multi-domain Translation for English and Vietnamese. This project is about how to collect high quality data and train a state-of-the-art neural machine translation model for Vietnamese. And it utilized Google Cloud TPU, Cloud Storage and related GCP products for faster training.

Kaggle announced the Google Open Source Prize early this year (Winners announcement page). In January, ML GDE Aakash Kumar Nain (India)’s Building models in JAX – Part1 (Stax) was awarded.

In February, ML GDE Victor Dibia (USA)’s notebook Signature Image Cleaning with Tensorflow 2.0 and ML GDE Sayak Paul (India) & Soumik Rakshit’s notebook gaugan-keras were awarded.

TFUG organizer Usha Rengaraju posted Variable Selection Networks (AI for Climate Change) and Probabilistic Bayesian Neural Networks using TensorFlow Probability notebooks on Kaggle. They both got gold medals, and she has become a Triple GrandMaster!

TFUG Chennai hosted the two events, Transformers – A Journey into attention and Intro to Deep Reinforcement Learning. Those events were planned for beginners. Events include introductory sessions explaining the transformers research papers and the basic concept of reinforcement learning.

ML GDE Margaret Maynard-Reid (USA), Nived P A, and Joel Shor posted Our Summer of Code Project on TF-GAN. This article describes enhancements made to the TensorFlow GAN library (TF-GAN) of the last summer.

ML GDE Aakash Nain (India) released a series of tutorials about building models in JAX. In the second tutorial, Aakash uses one of the most famous and most widely used high-level libraries for Jax to build a classifier. In the notebook, you will be taking a deep dive into Flax, too.

ML GDE Bhavesh Bhatt (India) built a model for braille to audio with 95% accuracy. He created a model that translates braille to text and audio, lending a helping hand to people with visual disabilities.

ML GDE Sayak Paul (India) recently wrote Publishing ConvNeXt Models on TensorFlow Hub. This is a contribution from the 30 versions of the model, ready for inference and transfer learning, with documentation and sample code. And he also posted First Steps in GSoC to encourage the fellow ML GDEs’ participation in Google Summer of Code (GSoC).

ML GDE Merve Noyan (Turkey) trained 40 models on keras.io/examples; built demos for them with Streamlit and Gradio. And those are currently being hosted here. She also held workshops entitled NLP workshop with TensorFlow for TFUG Delhi, TFUG Chennai, TFUG Hyderabad and TFUG Casablanca. It covered the basic to advanced topics in NLP right from Transformers till model hosting in Hugging Face, using TFX and TF Serve.

Machine Learning Communities: Q4 ‘21 highlights and achievements

Posted by HyeJung Lee, DevRel Community Manager and Soonson Kwon, DevRel Program Manager

Image shows graphic illustrating Q4 success. Includes an arrow pointing to a group of stick figures

Let’s explore highlights and achievements of vast Google Machine Learning communities over the last quarter of last year! We are excited and grateful about all the activities that the communities across the globe do.

Image of the Jax logo  next to images of animals and objects. The animals and objects are labelled Predictions

India-based Aakash Nain has completed the TF-Jax tutorial series with Part 9 (Autodiff in JAX) and Part 10 (Pytrees in JAX). Aakash also started a new tutorial series to learn about the existing methods of building models in JAX. The first tutorial Building models in JAX – Part1 (Stax) is released.

Christmas tree made of code next to words that say Advent of Code

On Dec 12th, ML GDE Paolo Galeone started to solve puzzles of the Advent of Code series using “pure TensorFlow” (without any other library). His solution has been updated in a series of 12 on his blog. He explained how he designed the solutions, how he implemented them, and – when needed – focused on some TensorFlow features not widely used. (Day 1, Day 2, Day 3, Day 4, Day 5, Day 6, Day 7, Day 8, Day 9, Day 10, Day 11, Day 12, Wrap up)

Detailed  diagram of batch prediction/evaluation pipeline leading to model training pipeline

ML GDE Chansung Park (Korea) & Sayak Paul (India) published an “Continuous Adaptation for Machine Learning System to Data Changes” article on TensorFlow blog. They presented a project that implements a workflow combining batch prediction and model evaluation for continuous evaluation retraining In order to capture changes in the data.

Image of Elyes Manais' Google Cloud Certification

ML GDE Elyes Manai from Tunisia wrote an article on GDE blog about his experience on the Google Cloud ML Engineer certification covering guide to certificate and tips.

Image collage of medical staff wearing PPE

TFUG organizer Ali Mustufa Shaikh and Rishit Dagli released “CPPE-5: Medical Personal Protective Equipment Dataset” (paper, code). This paper got featured on Google Research TRC’s publication section on January 5, 2022.

Image of a Google slide with text reading Ok, but what are transformers?

TFUG New York hosted a series of events in Dec. End-to-End NLP Workshop with TensorFlow. Brief introduction to the Kaggle competition for Great Barrier Reef challenge by Google(Slide). TF idea for ML Projects with GCP.

Left side of image shows a screenshot  from the Google for Startups Accelerator:MENA page. Right side of mage shows man with glasses holding a piece of paper in front of a wall that has signs on it that say hashtag creativity and hashtag technology

ML GDE Elyes Manai from Tunisia wrote an article “The ability to change people’s lives and leave one’s mark“. Are you facing difficulties growing in constrained environments? And do you think you’re not a first-class student and you don’t have connections in the industry? Then, check out Elyes’s story. He shared how Google helped him accelerate his impact.

Image shows a graph with data. Labels are on the side to denote wing, body, and tail

ML GDE Sayak Paul (India) and Soumik Rakshit’s Point Cloud Segmentation implemented the PointNet architecture for segmenting 3D point clouds using the ShapeNetCore dataset with TensorFlow 2.x. It is a winner of #TFCommunitySpotlight too.

Screenshot from a paper titled What Should Not be Contrastive in Contrastive Learning

Annotated Research Papers by ML GDE Aakash Kumar Nain (India) is an effort to make papers more accessible to a wider community. It also supports the web version and includes papers from Google Research and etc. This repository is popular enough to have a +2k star and a +200 fork.

Graphic wih text that reads A DevLibrary video interview wth Shai Reznik

Interview series of DevLibrary contributors : Meet the ML GDE Shai Reznik (Israel) and Doug Duhaime. And check out what they built with Google technology and what made them passionate.

Image of a TensorFlow 2.0 Global Docs Sprint event invite with Vikram Tiwari

ML DevFest 2021 by GDG Cloud San Francisco. There are 5 sessions that walk you through framing ML problems, researching ML, building proofs of concepts using existing ML APIs and models, building ML pipelines and etc. ML GDE Vikram Tiwari (USA) presented Vertex, ML Ops and GCP.

The words using Machine Learning for COVID19 helpline with Krupal Modi next to a picture of a man holding a microphone

Krupal Modi (India)’s blog article and #IamaGDE video shares how he’s been leading the machine learning initiatives at Haptik, a conversational AI platform, and how the team paired with the Indian Government and WhatsApp to build a COVID-19 helpline.

Hashtag I am a GDE next to a photo of a woman with sunglasses on her head

Leigh Johnson from USA is the founder of Print Nanny, an automated failure detection system and monitoring system for 3D printers. Meet Leigh in this blog and video!

ML Olympiad: Globally Distributed ML Competitions by the Community

Posted by Hee Jung, DevRel Community Manager

Blog header image shows graphic illustration of people, a group, and a medal

We are happy to announce ML Olympiad, an associated Kaggle Community Competitions hosted by Machine Learning Google Developer Experts (ML GDE) and TensorFlow User Group (TFUG).

Kaggle recently announced “Community Competitions” allowing anyone to create and host a competition at no cost. And our proud members of ML communities decided to dive in and take advantage of the feature to solve critical issues of our time, providing opportunities to train developers.

Why the ML Olympiad?

To train ML for developers leveraging Kaggle’s community competition. This is an opportunity for the participants to practice ML. This is the first 2022 global campaign of the ML Ecosystem team and this helps build stronger communities.

Image with text that reads Community Competitions make machine learning fun

ML Olympiad Community Competitions

Currently, 16 ML Olympiad community competitions are open, hosted by ML GDEs and TFUGs.

Arabic_Poems (in local language) link

  • Predict the name of a poet for Arabic poems. Encourage people to practice on Arabic NLP using TF.
  • Hosts: Ruqiya Bin Safi (ML GDE), Eyad Sibai, Hussain Alfayez / Saudi TFUG & Applied ML/AI group

Sky Survey link

  • Stellar classification with the digital sky survey
  • Hosts: Jieun Yoo, Michael Mellinger / NYTFUG

Análisis epidemiológico Guatemala (in local language) link

  • Make an analysis and prediction of epidemiological cases in Guatemala and the relations.
  • Hosts: Alvin Estrada, Julio Monterroso / TensorFlow User Group Guatemala

QUALITY EDUCATION (in local language) link

  • Competition will be focused on the Enem (National High School Examination) data. Competitors will have to create models to predict student scores in multiple tests.
  • Hosts: Vinicius Fernandes Caridá (ML GDE), Pedro Gengo, Alex Fernandes Mansano / Tensorflow User Group São Paulo

Landscape Image Classification link

  • Classification of partially masked natural images of mountains, buildings, seas, etc.
  • Hosts: Aditya Kane, Yogesh Kulkarni (ML GDE), Shashank Sane / TFUG Pune

Autism Prediction Challenge link

  • Classifying whether individuals have Autism or not.
  • Hosts: Usha Rengaraju, Vijayabharathi Karuppasamy, Samuel T / TFUG Mysuru and TFUG Chennai

Tamkeen Fund Granted link

  • Predict the company funds based on the company’s features
  • Hosts: Mohammed buallay (ML GDE), Sayed Ali Alkamel (ML GDE)

Hausa Sentiment Analysis (in local language) link

  • Classify the sentiment of sentences of Hausa Language
  • Hosts: Nuruddeen Sambo, Dattijo Murtala Makama / TFUG Bauchi

TSA Classification (in local language) link

  • We invite participants to develop a classification method to identify early autistic disorders.
  • Hosts: Yannick Serge Obam (ML GDE), Arnold Junior Mve Mve

Let’s Fight lung cancer (in local language) link

  • Spotting factors that are link to lung cancer detection
  • Hosts: abderrahman jaize, Sara EL-ATEIF / TFUG Casablanca

Genome Sequences classification (in local language) link

  • Genome sequence classification based on NCBI’s GenBank database
  • Hosts: Taha Bouhsine, Said ElHachmey, Lahcen Ousayd / TensorFlow User Group Agadir

GOOD HEALTH AND WELL BEING link

  • Using ML to predict heart disease – If a patient has heart disease or not
  • Hosts: Ibrahim Olagoke, Ahmad Olanrewaju, Ernest Owojori / TensorFlow User Group Ibadan

Preserving North African Culture link

  • We are tackling cultural preservation through a machine learning model capable of identifying the origin of a given item (food, clothing, building).
  • Hosts: elyes manai (ML GDE), Rania Boughanmi, Kayoum Djedidi / IEEE ESSTHS + GDSC ENIT

Delivery Assignment Prediction link

  • The aim of this competition is to build a multi-class classification model capable of accurately predicting the most suitable driver for one or several given orders based on the destination of the order and the paths covered by the deliverers.
  • Host: Thierno Ibrahima DIOP (ML GDE)

Used car price link

  • Predicting the price of an imported used car.
  • Hosts: Armel Yara, Kimana Misago, Jordan Erifried / TFUG Abidjan

TensorFlow Malaysia User Group link

  • Using AI/ML to solve Business Data problem
  • Hosts: Poo Kuan Hoong (ML GDE), Yu Yong Poh, Lau Sian Lun / TensorFlow & Deep Learning Malaysia User Group

Navigating ML Olympiad

You can search “ML Olympiad” on Kaggle Community Competitions page to see them all. And for further info, look for #MLOlympiad on social media.

Google Developers support ML Olympiad by providing swag for top 3 winners of each competition. Find your interest among the competitions, join/share them, and get your part of the swag for competition winners!

Machine Learning Communities: Q3 ‘21 highlights and achievements

Posted by HyeJung Lee, DevRel Community Manager and Soonson Kwon, DevRel Program Manager

Let’s explore highlights and achievements of vast Google Machine Learning communities by region for the last quarter. Activities of experts (GDE, professional individuals), communities (TFUG, TensorFlow user groups), students (GDSC, student clubs), and developers groups (GDG) are presented here.

Key highlights

Image shows a banner for 30 days of ML with Kaggle

30 days of ML with Kaggle is designed to help beginners study ML using Kaggle Learn courses as well as a competition specifically for the participants of this program. Collaborated with the Kaggle team so that +30 the ML GDEs and TFUG organizers participated as volunteers as online mentors as well as speakers for this initiative.

Total 16 of the GDE/GDSC/TFUGs run community organized programs by referring to the shared community organize guide. Houston TensorFlow & Applied AI/ML placed 6th out of 7573 teams — the only Americans in the Top 10 in the competition. And TFUG Santiago (Chile) organizers participated as well and they are number 17 on the public leaderboard.

Asia Pacific

Image shows Google Cloud and Coca-Cola logos

GDE Minori MATSUDA (Japan)’s project on Coca-Cola Bottlers Japan was published on Google Cloud Japan Blog covering creating an ML pipeline to deploy into real business within 2 months by using Vertex AI. This is also published on GCP blog in English.

GDE Chansung Park (Korea) and Sayak Paul (India) published many articles on GCP Blog. First, “Image search with natural language queries” explained how to build a simple image parser from natural language inputs using OpenAI’s CLIP model. From this second “Model training as a CI/CD system: (Part I, Part II)” post, you can learn more about why having a resilient CI/CD system for your ML application is crucial for success. Last, “Dual deployments on Vertex AI” talks about end-to-end workflow using Vertex AI, TFX and Kubeflow.

In China, GDE Junpeng Ye used TensorFlow 2.x to significantly reduce the codebase (15k → 2k) on WeChat Finder which is a TikTok alternative in WeChat. GDE Dan lee wrote an article on Understanding TensorFlow Series: Part 1, Part 2, Part 3-1, Part 3-2, Part 4

GDE Ngoc Ba from Vietnam has contributed AI Papers Reading and Coding series implementing ML/DL papers in TensorFlow and creates slides/videos every two weeks. (videos: Vit Transformer, MLP-Mixer and Transformer)

A beginner friendly codelabs (Get started with audio classification ,Go further with audio classification) by GDSC Sookmyung (Korea) learning to customize pre-trained audio classification models to your needs and deploy them to your apps, using TFlite Model Maker.

Cover image for Mat Kelcey's talk on JAX at the PyConAU event

GDE Matthew Kelcey from Australia gave a talk on JAX at PyConAU event. Mat gave an overview to fundamentals of JAX and an intro to some of the libraries being developed on top.

Image shows overview for the released PerceiverIO code

In Singapore, TFUG Singapore dived back into some of the latest papers, techniques, and fields of research that are delivering state-of-the-art results in a number of fields. GDE Martin Andrews included a brief code walkthrough for the released PerceiverIO code at perceiver– highlighting what JAX looks like, how Haiku relates to Sonnet, but also the data loading stuff which is done via tf.data.

Machine Learning Experimentation with TensorBoard book cover

GDE Imran us Salam Mian from Pakistan published a book “Machine Learning Experimentation with TensorBoard“.

India

GDE Aakash Nain has published the TF-JAX tutorial series from Part 4 to Part 8. Part 4 gives a brief introduction about JAX (What/Why), and DeviceArray. Part 5 covers why pure functions are good and why JAX prefers them. Part 6 focuses on Pseudo Random Number Generation (PRNG) in Numpy and JAX. Part 7 focuses on Just In Time Compilation (JIT) in JAX. And Part 8 covers vmap and pmap.

Image of Bhavesh's Google Cloud certificate

GDE Bhavesh Bhatt published a video about his experience on the Google Cloud Professional Data Engineer certification exam.

Image shows phase 1 and 2 of the Climate Change project using Vertex AI

Climate Change project using Vertex AI by ML GDE Sayak Paul and Siddha Ganju (NVIDIA). They published a paper (Flood Segmentation on Sentinel-1 SAR Imagery with Semi-Supervised Learning) and open-sourced the project with regard to NASA Impact’s ETCI competition. This project made four NeurIPS workshops AI for Science: Mind the Gaps, Tackling Climate Change with Machine Learning, Women in ML, and Machine Learning and the Physical Sciences. And they finished as the first runners-up (see Test Phase 2).

Image shows example of handwriting recognition tutorial

Tutorial on handwriting recognition was contributed to Keras example by GDE Sayak Paul and Aakash Kumar Nain.

Graph regularization for image classification using synthesized graphs by GDE Sayak Pau was added to the official examples in the Neural Structured Learning in TensorFlow.

GDE Sayak Paul and Soumik Rakshit shared a new NLP dataset for multi-label text classification. The dataset consists of paper titles, abstracts, and term categories scraped from arXiv.

North America

Banner image shows students participating in Google Summer of Code

During the GSoC (Google Summer of Code), some GDEs mentored or co-mentored students. GDE Margaret Maynard-Reid (USA) mentored TF-GAN, Model Garden, TF Hub and TFLite products. You can get some of her experience and tips from the GDE Blog. And you can find GDE Sayak Paul (India) and Googler Morgan Roff’s GSoC experience in (co-)mentoring TensorFlow and TF Hub as well.

A beginner friendly workshop on TensorFlow with ML GDE Henry Ruiz (USA) was hosted by GDSC Texas A&M University (USA) for the students.

Screenshot from Youtube video on how transformers work

Youtube video Self-Attention Explained: How do Transformers work? by GDE Tanmay Bakshi from Canada explained how you can build a Transformer encoder-based neural network to classify code into 8 different programming languages using TPU, Colab with Keras.

Europe

GDG / GDSC Turkey hosted AI Summer Camp in cooperation with Global AI Hub. 7100 participants learned about ML, TensorFlow, CV and NLP.

Screenshot from slide presentation titled Why Jax?

TechTalk Speech Processing with Deep Learning and JAX/Trax by GDE Sergii Khomenko (Germany) and M. Yusuf Sarıgöz (Turkey). They reviewed technologies such as Jax, TensorFlow, Trax, and others that can help boost our research in speech processing.

South/Central America

Image shows Custom object detection in the browser using TensorFlow.js

On the other side of the world, in Brazil, GDE Hugo Zanini Gomes wrote an article about “Custom object detection in the browser using TensorFlow.js” using the TensorFlow 2 Object Detection API and Colab was posted on the TensorFlow blog.

Screenshot from a talk about Real-time semantic segmentation in the browser - Made with TensorFlow.js

And Hugo gave a talk about Real-time semantic segmentation in the browser – Made with TensorFlow.js covered using SavedModels in an efficient way in JavaScript directly enabling you to get the reach and scale of the web for your new research.

Data Pipelines for ML was talked about by GDE Nathaly Alarcon Torrico from Bolivia explained all the phases involved in the creation of ML and Data Science products, starting with the data collection, transformation, storage and Product creation of ML models.

Screensho from TechTalk “Machine Learning Competitivo: Top 1% en Kaggle (Video)

TechTalk “Machine Learning Competitivo: Top 1% en Kaggle (Video)“ was hosted by TFUG Santiago (Chile). In this talk the speaker gave a tour of the steps to follow to generate a model capable of being in the top 1% of the Kaggle Leaderboard. The focus was on showing the libraries and“ tricks ”that are used to be able to test many ideas quickly both in implementation and in execution and how to use them in productive environments.

MENA

Screenshot from workshop about Recurrent Neural Networks

GDE Ruqiya Bin Safi (Saudi Arabia) had a workshop about Recurrent Neural Networks : part 1 (Github / Slide) at the GDG Mena. And Ruqiya gave a talk about Recurrent Neural Networks: part 2 at the GDG Cloud Saudi (Saudi Arabia).

AI Training with Kaggle by GDSC Islamic University of Gaza from Palestine. It is a two month training covering Data Processing, Image Processing and NLP with Kaggle.

Sub-Saharan Africa

TFUG Ibadan had two TensorFlow events : Basic Sentiment analysis with Tensorflow and Introduction to Recommenders Systems with TensorFlow”.

Image of Yannick Serge Obam Akou's TensorFlow Certificate

Article covered some tips to study, prepare and pass the TensorFlow developer exam in French by ML GDE Yannick Serge Obam Akou (Cameroon).

Become a Developer Student Club Lead

Posted by Erica Hanson, Global Program Lead, Developer Student Clubs

Calling all student developers: If you’re someone who wants to lead, is passionate about technology, loves problem-solving, and is driven to give back to your community, then Developer Student Clubs has a home for you. Interest forms for the upcoming 2020-2021 academic year are now available. Ready to dive in? Get started at goo.gle/dsc-leads.

Want to know more? Check out these details below.

Image description: People holding up Developer Students Club sign

What are Developer Student Clubs?

Developer Student Clubs (DSC) are university based community groups for students interested in Google developer technologies. With programs that meet in person and online, students from all undergraduate and graduate programs with an interest in growing as a developer are welcome. By joining a DSC, students grow their knowledge in a peer-to-peer learning environment and build solutions for local businesses and their community.

Why should I join?

– Grow your skills as a developer with training content from Google.

– Think of your own project, then lead a team of your peers to scale it.

– Build prototypes and solutions for local problems.

– Participate in a global developer competition.

– Receive access to select Google events and conferences.

– Gain valuable experience

Is there a Developer Student Club near me?

Developer Student Clubs are now in 68+ countries with 860+ groups. Find a club near you or learn how to start your own, here.

When do I need to submit the interest form?

You may express interest through the form until May 15th, 11:59pm PST. Get started here.

Make sure to learn more about our program criteria.

Our DSC Leads are working on meaningful projects around the world. Watch this video of how one lead worked to protect her community from dangerous floods in Indonesia. Similarly, read this story of how another lead helped modernize healthcare in Uganda.

We’re looking forward to welcoming a new group of leads to Developer Student Clubs. Have a friend who you think is a good fit? Pass this article along. Wishing all developer students the best on the path towards building great products and community.

Submit interest form here.

*Developer Student Clubs are student-led independent organizations, and their presence does not indicate a relationship between Google and the students’ universities.

DevFest 2019: It’s time for Latin America!

DevFest bannerPosted by Mariela Altamirano, Community Manager for Latin America with Grant Timmerman, Developer Programs Engineer and Mete Atamel, Developer Advocate

DevFest season is always full of lively surprises with enchanting adventures right around the corner. Sometimes these adventures are big: attending a DevFest in the Caribbean, in the heart of the amazon jungle, or traveling more than 3,000 meters above sea level to discover the beautiful South American highlands. Other times they are small but precious: unlocking a new way of thinking that completely shifts how you code.

October marks the beginning of our DevFest 2019 season in Latin America, where all of these experiences become a reality thanks to the efforts of our communities.

What makes DevFests in LATAM different? Our community is free spirited, eager to explore the natural landscapes we call home, proud of our deep cultural diversity, and energized by our big cities. At the same time, we are connected to the tranquil spirit of our small towns. This year, we hope to reflect this way of life through our 55 official Latin America DevFests.

During the season, Latin America will open its doors to Google Developer Experts, Women Techmakers, Googlers, and other renowned speakers, to exchange ideas on Google products such as Android, TensorFlow, Flutter, Google Cloud Platform. Activities include, hackathons, codelabs and training sessions. This season, we will be joined by Googlers Grant Timmerman and Mete Atamel.

Grant is a Developer Programs Engineer at Google where he works on Cloud Functions, Cloud Run, and other serverless technologies on Google Cloud Platform. He loves open source, Node, and plays the alto saxophone in his spare time. During his time in Latin America, he’ll be discussing all things serverless at DevFests and Cloud Summits in Chile, Argentina, Peru, Colombia, and Mexico.

Grant Timmerman, developer programs engineer

Mete Atamel, developer advocate

Mete is a Developer Advocate based in London. He focuses on helping developers with Google Cloud. At DevFest Sul in Floripa and other conferences and meetups throughout Brazil in October, he’ll be talking about serverless containers using Knative and Cloud Run. He first visited the region back in 2017 when he visited Sao Paulo

Afterwards, he went to Rio de Janeiro and immediately fell in love with the city, its friendly people and its positive vibe. Since then, he spoke at a number of conferences and meetups in Mexico, Colombia, Peru, Argentina, Uruguay and Brazil, and always has been impressed with the eagerness of people to learn more.

This year we will be visiting new countries such as Jamaica, Haiti, Guyana, Honduras, Venezuela and Ecuador that have created their first GDG (Google Developer Group) communities. Most of these new communities are celebrating their first DevFest! We’ll also be hosting diversity and inclusion events, so keep an eye out for more details!

We thank everyone for being a part of DevFest and our community.

We hope you join us!

#DevFest

#DevFestLATAM

Find a DevFest near you at g.co/dev/fest/sa