StatMike
StatMike
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End-to-End: Pipeline Orchestration (KFP) - BigQuery (BQML) Model For Endpoint Update [notebook 03C]
In [notebook 03a] we trained a model using BigQuery ML (BQML). In [notebook 03b] we used Vertex AI to upload the BQML model and deploy it to a live endpoint for online predictions. In this [notebook 03c] we will build a Kubeflow Pipeline (KFP) to conditionally replace the model on the online endpoint with a better model. Vertex AI Pipelines is a service that runs Kubeflow pipelines as a managed service where we don’t have to worry about infrastructure. This makes it incredibly straight-forward to build a pipelines to orchestrate all the steps of a challenger model scenario:
➡️ Train a Challenger Model
➡️ Retrieve evaluation metrics for the Challenger Model
➡️ Retrieve evaluation metrics for the current model
➡️ Compare the models
➡️ Evaluate if the Challenger model is better than the current model
➡️ If better, update the online endpoint
➡️➡️ Deploy the challenger model
➡️➡️ Move all traffic to the challenger model
➡️➡️ Undeploy the previous model
GitHub Repository: github.com/statmike/vertex-ai-mlops
The Notebook followed in this video is an older version - link for the version in the video: github.com/statmike/vertex-ai-mlops/blob/fd442b458c710a0a7afdc41bae690d2a3282e93c/03c%20-%20BQML%20%2B%20Vertex%20AI%20%3E%20Pipelines%20-%20automated%20pipelines%20for%20updating%20models.ipynb
An updated version of the notebook can be found here: github.com/statmike/vertex-ai-mlops/blob/main/03%20-%20BigQuery%20ML%20(BQML)/03Tools%20-%20Pipelines%20Example%202.ipynb
Timeline:
0:00 - Introduction
0:44 - Overview
2:20 - Start Walkthrough
11:18 - [Notebook Section] Setup
13:30 - [Notebook Section] Custom Components
23:07 - [Notebook Section] Pipeline Definition
27:55 - [Notebook Section] Compile Pipeline
29:30 - [Notebook Section] Create Vertex AI Pipeline Job
30:08 - Review Pipeline Run with Console
49:50 - Re-run Pipeline (Endpoint Update)
58:20 - Q&A: When would I want to run a pipeline like this?
1:03:35 - [Notebook Section] Prediction
1:10:50 - Wrap-up
มุมมอง: 3 357

วีดีโอ

End-to-End: ML with TensorFlow in Jupyter with Tensorflow I/O BigQuery Reader [notebook 05]
มุมมอง 4K2 ปีที่แล้ว
An end-to-end workflow using a Jupyter Notebook hosted by Vertex AI Workbench to train an ML model with TensorFlow within the notebook. Training data is read using the TensorFlow I/O reader for BigQuery. Many deep explanations along the way including using Tensorboard to evaluate the model training. The final model is deployed to a Vertex AI Endpoint and online predictions are demonstrated usin...
Part 2 - End-To-End: Pipeline Orchestration (KFP) - AutoML in Vertex AI for ML Ops [notebook 02c]
มุมมอง 2K2 ปีที่แล้ว
Today we revisit a previous video and add a section for model evaluation using the Vertex AI API. See how easy it is to retrieve a vast array of evaluation metrics for AutoML models. The original video: th-cam.com/video/1gHJgY7AXAs/w-d-xo.html An end-to-end workflow using Pipelines within Vertex AI on Google Cloud Platform. We will use AutoML to train a machine learning model. A walkthrough of ...
Part 2 - End-To-End: Interactive Code (Python) - AutoML in Vertex AI for ML Ops [notebook 02b]
มุมมอง 2.7K2 ปีที่แล้ว
Today we revisit a previous video and add a section for model evaluation using the Vertex AI API. See how easy it is to retrieve a vast array of evaluation metrics for AutoML models. The original video: th-cam.com/video/GOxHYfCLc6U/w-d-xo.html An end-to-end workflow using Python clients for Vertex AI on Google Cloud Platform. We will use AutoML to train a machine learning model. A walkthrough o...
ML with SQL in BigQuery to Online Predictions in Vertex AI for ML Operations [notebook 03b]
มุมมอง 2.8K2 ปีที่แล้ว
An end-to-end workflow using the Python clients for Vertex AI on Google Cloud Platform. We export a model created with BigQuery ML and use it for online predictions in Vertex AI. This video follows the notebook 03b - Vertex AI BigQuery Machine Learning (BQML) - Online Predictions with BQML Models. The Notebook followed in this video is an older version - link for the version in the video: githu...
End-To-End: ML with SQL in BigQuery (BQML) [notebook 03a]
มุมมอง 6K2 ปีที่แล้ว
An end-to-end workflow using the Python client for BigQuery on Google Cloud Platform. We use BigQuery ML to train a model using SQL! A walkthrough of all the steps from connecting to data sources, training a model, evaluating the final model, and requesting predictions from multiple clients. A few deep dives along the way including model explainability! This video follows the notebook 03a - Big...
End-To-End: Pipeline Orchestration (KFP) - AutoML in Vertex AI for ML Operations [notebook 02c]
มุมมอง 10K2 ปีที่แล้ว
An end-to-end workflow using Pipelines within Vertex AI on Google Cloud Platform. We will use AutoML to train a machine learning model. A walkthrough of building a repeatable pipeline to orchestrate all the steps from connecting to data sources, training a model, evaluating the final model, deploying to an online endpoint and requesting predictions from multiple clients. A few deep dives along ...
End-To-End: Interactive Code (Python) - AutoML in Vertex AI for ML Operations [notebook 02b]
มุมมอง 8K2 ปีที่แล้ว
An end-to-end workflow using Python clients for Vertex AI on Google Cloud Platform. We will use AutoML to train a machine learning model. A walkthrough of all the steps from connecting to data sources, training a model, evaluating the final model, deploying to an online endpoint and requesting predictions from multiple clients. A few deep dives along the way including model explainability! This...
End-To-End: No Code - AutoML in Vertex AI for ML Operations [notebook 02a]
มุมมอง 27K2 ปีที่แล้ว
An end-to-end workflow completely within the Vertex AI interface in the Google Cloud Console. We will use AutoML to train a machine learning model. A walkthrough of all the steps from connecting to data sources, training a model, evaluating the final model, deploying to an online endpoint and requesting predictions from multiple clients. A few deep dives along the way! This video follows the no...
Introduction - Vertex AI for ML Operations
มุมมอง 43K2 ปีที่แล้ว
Introduction to the playlist of end-to-end workflow walkthroughs for machine learning operations using Google Cloud Platform’s Vertex AI. GitHub Repository: github.com/statmike/vertex-ai-mlops Timeline: 0:00 - Introduction 3:25 - The GitHub Repository 4:40 - Walkthrough List of Workflows 6:40 - Q&A - What is not covered 7:30 - Q&A - Are all the videos needed? 8:12 - Q&A - How do I learn ML? 12:...
Environment Setup - Vertex AI for ML Operations [notebook 00]
มุมมอง 25K2 ปีที่แล้ว
A walkthrough of creating a Google Cloud Platform project and setting up the environment for this series of end-to-end workflows. This video follows the readme and the first notebook [00 - Environment Setup] in the repository. GitHub Repository: github.com/statmike/vertex-ai-mlops The Notebook followed in this video: github.com/statmike/vertex-ai-mlops/blob/main/00 - Setup/00 - Environment Setu...
Data Source - Vertex AI for ML Operations [notebook 01]
มุมมอง 13K2 ปีที่แล้ว
A walkthrough of creating the data source for this project using BigQuery. We will import, review, and prepare the data for use in machine learning workflows. This video follows the notebook [01 - BigQuery - Table Data Source] in the repository. GitHub Repository: github.com/statmike/vertex-ai-mlops The Notebook followed in this video: github.com/statmike/vertex-ai-mlops/blob/main/01 - Data Sou...

ความคิดเห็น

  • @austin4018
    @austin4018 28 วันที่ผ่านมา

    Only reason im about to skip is because ive watched 3:25 got a hour left (with ads) almost 6% of this video spent offering me nothing. Only reason i didnt skip is the commenters.... But im tired so goin to slee not book markin ya so maybe ill come back

  • @TheBuckonator
    @TheBuckonator หลายเดือนก่อน

    This is a great video, thanks for your efforts! I have a question, is there a way to see the type of model that was used?

  • @MrDibragimov
    @MrDibragimov หลายเดือนก่อน

    Hey Mike, just wanted to encourage you to keep going. We need people to share knowledge. Maybe the feedback does not come immediately after the release of the video, i found it 2 years after publishing, but you are doing a great work, keep doing...

  • @iqbalassyraf5058
    @iqbalassyraf5058 2 หลายเดือนก่อน

    Amazing Mike, thank you very much for the course.

  • @lifelonglearning4379
    @lifelonglearning4379 2 หลายเดือนก่อน

    Mike, Great video and github repo is great. Noticed the current version of repository (as on 10/09/2024) has some differences from the one taught in the class.

  • @verbundo7694
    @verbundo7694 2 หลายเดือนก่อน

    Great videos. I've learned a lot here. What I am asking myself, given the small number of frauds in the dataset, doesn't it make sense to verify that we'e got a similar ratio of frauds in all 3 subsets after dividing a dataset? Because it is possible, that test data will contain just a very small amount of frauds, or none?

  • @MeraAashiyan
    @MeraAashiyan 2 หลายเดือนก่อน

    Your videos helped me through my dissertation ❤ so detailed , indepth and knowledgeable

  • @sandymlgenai
    @sandymlgenai 2 หลายเดือนก่อน

    In love with your work! High quality content! It would be great if you could create content on other topics too!

  • @rajmahalingam3936
    @rajmahalingam3936 3 หลายเดือนก่อน

    How to schedule a batch prediction job?/predict a number of records at a time after deployment?

  • @heitordata
    @heitordata 3 หลายเดือนก่อน

    You deserve tons of cookies, Mike! I really appreciate your job! Thanks!

  • @heitordata
    @heitordata 3 หลายเดือนก่อน

    Hey, Mike! I have just finished this first Intro video and I want to thank you so much for this content! Right now, I'm looking for content to learn more model deployment on Cloud using Google Cloud and I believe I'll find such a rich content here and perhaps the answers that will help me solve the problems I'm facing right now. Thank you so much, and keep it up! The ML Community needs more people like you!

  • @jjj12345-p
    @jjj12345-p 3 หลายเดือนก่อน

    Very great introduction for BigQuery, I am interested in how BigQuery is compared against SnowFlake these days or other products in the market?

  • @algorithmo134
    @algorithmo134 3 หลายเดือนก่อน

    Hi Mike do you know why I keep getting quota limit exceeded errors?

  • @GAURAVKUMARSVNIT
    @GAURAVKUMARSVNIT 3 หลายเดือนก่อน

    I need to create a legal chatbot for indian context hence for that i need to do data collection that is going to be textual it can be Indian panel codes various court vertdict in pdf format various IPC section with punishment and similar registered crimes in any part of the country. so how can i collect that?

  • @ahmedyosri7479
    @ahmedyosri7479 3 หลายเดือนก่อน

    Thanks Mike. Hope new videos are coming soon!

  • @algorithmo134
    @algorithmo134 4 หลายเดือนก่อน

    Hi, instead of using bigQuery, can we use Cloud storage to store csv datasets then use it in the notebook? Looking forward to the csv video. ❤

    • @statmike-channel
      @statmike-channel 4 หลายเดือนก่อน

      Absolutely! This video showed how to setup the TFio BQ reader but since it's Python you can read from anywhere you have connection to. And loading from GCS is made super easy with the automatic mounting: cloud.google.com/vertex-ai/docs/training/cloud-storage-file-system

  • @algorithmo134
    @algorithmo134 4 หลายเดือนก่อน

    Hi Mike, nice video! instead of storing the data in sql, is it possible to store in csv?

    • @statmike-channel
      @statmike-channel 4 หลายเดือนก่อน

      Definitely! While the video shows BQ, it is also possible to use CSV in cloud storage. Here is a link that will help: cloud.google.com/vertex-ai/docs/tabular-data/classification-regression/prepare-data#import-source

    • @algorithmo134
      @algorithmo134 4 หลายเดือนก่อน

      @@statmike-channel I would like to see a video on building a complete pipeline of fetching data from an api and storing it in big query and using that data to train the model and deploying it to an endpoint. Hopefully you will make one.

  • @algorithmo134
    @algorithmo134 4 หลายเดือนก่อน

    Hi Mike thank you for your video. I have a question is there a way to fetch data from an api and used it in vertex ai instead of uploading a dataset? Also how do I automate the fetching process for example like a weather app?

    • @statmike-channel
      @statmike-channel 4 หลายเดือนก่อน

      I noticed this comment is for an automl video. If for training you would need to pre gather the data and store it. For serving you could create an endpoint the does fetching as part of the serving. I like using FastAPI with a custom container for prediction: cloud.google.com/vertex-ai/docs/predictions/use-custom-container

    • @algorithmo134
      @algorithmo134 4 หลายเดือนก่อน

      @@statmike-channel can you make a video about it? I would really love to see your videos on it. Loving the playlist so far!

    • @algorithmo134
      @algorithmo134 3 หลายเดือนก่อน

      @@statmike-channel Hi is fastAPI required? Can we just serve using vertex AI?

  • @legendrytitan163
    @legendrytitan163 4 หลายเดือนก่อน

    i usually dont comment,But Mike I need more vedios from youuuu!!

  • @WilfredLoyYongKang
    @WilfredLoyYongKang 4 หลายเดือนก่อน

    Awesome Mike! Even after 2 years, this is one of the best! Thanks Mike!

  • @RussellMiller-e8f
    @RussellMiller-e8f 4 หลายเดือนก่อน

    When modifying the version data using the suggestions (which describes false pos. false neg. and true pos.) located in the "labels" under model registry/evaluate/(selected label... i.e. '0' or '1'), where are the changes reflected (if any at all)? I don't see any changes being made to the dataset that the version was trained in after making changes. How can you use these changes and continue modifying the dataset alongside the changes made with the suggestions?

  • @dhawlandrashrivastav
    @dhawlandrashrivastav 4 หลายเดือนก่อน

    Thank you brother from India

  • @LiangOu-f2c
    @LiangOu-f2c 4 หลายเดือนก่อน

    If anyone try to the notebook the first time from 2024, it won't work. You have to click "Open in Vertex AI Workbench" and let it deploy the notebook first.

  • @sambasg607
    @sambasg607 4 หลายเดือนก่อน

    Very informative ! Thanks for sharing

  • @mshahid-mohana
    @mshahid-mohana 5 หลายเดือนก่อน

    bravo... the content is brilliant. method is effective. larger "font_size" could have more convinient.

  • @abdullahmobark6183
    @abdullahmobark6183 5 หลายเดือนก่อน

    What kind of experince do i need to take on this serious ? I work on IT filed but no experince on mechine learnig or coding ?

  • @jawadasif8130
    @jawadasif8130 5 หลายเดือนก่อน

    Thanks you for your great tutorials. I want to migrate a project from legacy to vertex ai. is there any migration tool kit or tutorial i can get to have basics. thank you

  • @9941521791
    @9941521791 5 หลายเดือนก่อน

    Hi Mike, wonderful videos and your knowledge is amazing in this field. Looking forward you to resume your videos :)

  • @eddieotudor9432
    @eddieotudor9432 6 หลายเดือนก่อน

    Thanks Mike for such great content. I’ve learnt a whole lot from this. Cheers!

  • @seanvw7905
    @seanvw7905 6 หลายเดือนก่อน

    Great stuff! Enjoyed excellent explanations and following along with github repo clone. I would have a few questions. 1) since I changed a few lines in notebooks, what happens if I commit changes: is git going to try updating your repo? 2) I would like to see the underlying model architecture: how to see this? Perhaps answers coming in following vidoes.

  • @elsaladon2936
    @elsaladon2936 6 หลายเดือนก่อน

    Great content, thank you very much!

  • @eddieotudor9432
    @eddieotudor9432 6 หลายเดือนก่อน

    Thanks so much Mike! This is just want I needed!

  • @eddieotudor9432
    @eddieotudor9432 6 หลายเดือนก่อน

    Thanks so much for this Mike! I'm super grateful!

  • @eddieotudor9432
    @eddieotudor9432 6 หลายเดือนก่อน

    Let's work together to make the practice of AI and ML more collaborative, accurate, and more approachable to a wider and more connected audience. _StatMike!

  • @paulsilva753
    @paulsilva753 6 หลายเดือนก่อน

    Thank you. I really appreciate your effort. 😊

  • @AngelDiMariaRM22
    @AngelDiMariaRM22 7 หลายเดือนก่อน

    Thank you for the playlist. Amazing quality. Just wanted to say that you are amazing and your content is appreciated.

  • @JesperRietbergen
    @JesperRietbergen 7 หลายเดือนก่อน

    Amazing content, incredibly valuable! Can't believe this is free 🙌💫

  • @JohnWedderburn
    @JohnWedderburn 8 หลายเดือนก่อน

    This is a great resource, looking forwards to checking out your other videos. Thanks so much for putting these up.

  • @АртемШлагин
    @АртемШлагин 8 หลายเดือนก่อน

    Thank you for the series! What tweaking did you do to the model in order to make it better than the previous one -- wouldn't the automl in BQ always produce the same result given the same training data?

  • @MugishaJean1
    @MugishaJean1 9 หลายเดือนก่อน

    I love this!

  • @hpaghababa8111
    @hpaghababa8111 10 หลายเดือนก่อน

    My feeling just after watching only the first video is that I will learn a lot by following the next videos in the play list. You are talking in an exciting and enjoyable way. I love the Bayes formula on the wall, that is the only simple formula that usually takes a bit of time for me to remember and it is my favorite probabilistic formula. Thanks for the making this video specially in your beautiful office.

  • @jimmydean4586
    @jimmydean4586 10 หลายเดือนก่อน

    I may have an astonishing project that does the impossible...I need a ML set up to take it to the next level... It took me forever to code the one of a kind tool but i really need a ML model to analyze it. I have not been able to get AI to work on it properly....probably because no one has EVER seen a data set like this .. i really need someone to help with this FULL NDA

  • @umr84
    @umr84 10 หลายเดือนก่อน

    Great Content. This is exactly what a beginner needs to start working with vertex AI.

  • @ReynEngelbrecht
    @ReynEngelbrecht 10 หลายเดือนก่อน

    Thanks man, this helped a lot.

  • @ErkangXia
    @ErkangXia 10 หลายเดือนก่อน

    I like this series, this is the series i dont watch with 2x playback speed

  • @xyz-jn4oj
    @xyz-jn4oj 10 หลายเดือนก่อน

    hey mike , i don't understand how you create folder under BigQuery? Can you explain?

  • @saurabhgupta9430
    @saurabhgupta9430 10 หลายเดือนก่อน

    Hi Mike, seems like the services, tool, and interface had a facelift. I could not locate the Notebook API within Workbench - New to the GCP Platform and trying to follow your videos with today's GCP ecosystem - Please advice. Thanks. BTW, awesome content!!!

  • @Dodo17sky
    @Dodo17sky 11 หลายเดือนก่อน

    Hello Mike! I followed your videos and after 2 model training sessions I got 72$ to pay to Google. I appreciate what you sharing with us but please mention this solution with Google Cloud Machine Learning is not for personal use because the costs are too high and regular guys who just want to learn ML can not afford this. I like the framework and the tools provided by google but if there is no way to just use my personal hardware to run the ML then is no point in learning these stuff. Once again I appreciate your effort to share the knowledge with us

  • @TheRidwanSpace
    @TheRidwanSpace 11 หลายเดือนก่อน

    already moved to MLOps engineer role, the github repo and videos help me a lot. Thanks mike

  • @prakashbaskar5548
    @prakashbaskar5548 11 หลายเดือนก่อน

    Hi Mike, this is excellent video. Is it possible to let the pipeline trigger automatically in case of data refresh either in google big query or in the source csv file?