<img height="1" width="1" style="display:none;" alt="" src="https://px.ads.linkedin.com/collect/?pid=2634489&amp;fmt=gif">

AI and Machine Learning, Session Recording

Vertex AI Drives Conversation at C2C Connect: France Session on International Women's Day

By Guillaume Blaquiere | March 31, 2022

On Tuesday, March 8, also known as International Women's Day, C2C France Team Leads  @antoine.castex  and @guillaume blaquiere  were excited to welcome Google Lead Developer Advocate @Priyanka Vergadia  to host a powerful session for the Google Cloud space in France and beyond. These sessions intend to bring together a community of cloud experts and customers to connect, learn, and shape the future of cloud. At this C2C Connect event, Vergadia led a broad and enthusiastic discussion about Vertex AI and the MLOps pipeline.

 

60 Minutes Summed Up in 60 Seconds

 

  1. ML and AI are the cornerstone technologies of any company that wants to leverage its data value.
  2. ML can be used across different platforms, including Google Cloud. BigQuery ML is a key example of serverless ML training and serving.
  3. Vertex AI is the primary end-to-end AI product on Google Cloud and interacts with many other Google Cloud products.
  4. Low-code and no-code users can reuse pre-trained Vertex AI models and customize them to fit their business use cases. It's perfect for beginner and no-ML engineer profiles.
  5. Advanced users can leverage Vertex AI's managed Jupyter Notebook to discover, analyze, and build their models.
  6. Vertex AI also allows users to train models at scale, to deploy serverless models, and to monitor drift and performance.
  7. As Vergadia reminded the audience, ML engineering makes up only 5% of the effort that goes into the ML workflow. The upstream steps (data cleaning, discovery, feature engineering preparation) and the downstream steps (monitoring, retraining, deployment, hyperparameter tuning) must be optimized to save time, effort, and money.
  8. To this end, VertexAI supports a pipeline definition, based on the TFX or Kube Flow pipelines, to automate the end-to-end tasks around ML engineering. This pipeline is called MLOps.

 

Watch the full recording of the session below:

 

 

Despite its 60-minute time limit, this conversation didn't stop. VertexAI is a hot topic, and it certainly kept everyone's attention. The group spent time discussing data warehouses, data analytics, and data lakes, focusing on products like BigQuery, Datastudio, and Cloud Storage. Attendees also offered their own feedback on the content of the session. For example, halfway through the presentation, Soumo Chakraborty asked how users can integrate ML pipelines in a CI/CD pipeline, and pipeline integration became a focal point of the remainder of the discussion.

 

Preview What's Next

 

These upcoming C2C events will cover other major topics of interest that didn't make it to the discussion floor this time around: 

  1. Make the Cloud Smarter, April 12, 2022

  2. Looker In the Real World with Looker PM Leigha Jarett, May 10, 2022 (In-person event in Paris)

If these are topics you're eager to explore at future events, be sure to sign up to our platform!

 

Extra Credit

 

Looking for more Google Cloud products news and resources? We got you. The following links were shared with attendees and are now available to you:


Recent Articles

Data Analytics

Generative AI: Are You Behind?!

Review the latest insights from the AI Readiness Report.
By Bruno Aziza
Industry Solutions

Make "Gen AI Work": Landscape, SLMs vs. LLMs, Cost & More...

Discover the 5 metrics you need to know in order to be an exceptional CEO and Operator.
By Bruno Aziza
Google Cloud Strategy

AI Cheat Sheet

AI is no more and no less the drive to create robots with human minds so they can do everything we do and more. Use this cheat sheet to help decode the space.
By Leah Zitter