What we're about

"Learn by Practice". Join us to learn and practice AI, Machine learning, Deep learning and Data Science technology together with like-minded developers.

Our goal is to congregate with AI enthusiasts from all over Portland to learn and practice AI tech, through tech talks, study jams, code labs etc.. we regularly invite tech leads from innovated companies, successful startups to share their practice experiences and practices in the world of AI, Cloud, Data, Blockchain.

If you’d like to speak at future meetups, co-promote your meetup or inquire about partnership opportunities, please feel free to reach out to us.

Thank you

**Learn applied AI tech online with 80000+ developers globally, via webinars, live online courses, bootcamps: https://learn.xnextcon.com
** AI Developer Conference (Seattle, San Francisco, New York, Beijing): http://www.xnextcon.com

Upcoming events (2)

(Virtual) AWS AI/ML Bootcamp: Build ML Pipeline with NLP, TensorFlow, SageMaker

**this is online event, make sure to register here: RSVP: https://learn.xnextcon.com/event/eventdetails/W20072021 Free virtual full day AWS AI/ML bootcamp. You can join from anywhere with zoom. This full day hands-on bootcamp is for developers of all skill level to come together to learn deep learning on NLP using Tensorflow with Amazon Sagemaker. Get free deep learning training. Together we will work through several deep learning labs, build an end-to-end AI/ML pipeline for natural language processing with Amazon SageMaker. You will get hands-on experience with the deep learning, NLP, BERT, Tensorflow and Sagemaker. Every attendee will receive a free AWS instance for this bootcamp The bootcamp includes 6 modules: 1) Ingest, analyze, and visualize a public dataset 2) Transform the raw dataset into machine learning features 3) Train a model with our features 4) Optimize model training using hyper-parameter tuning 5) Deploy and test our model both online (real-time) and offline (batch) 6) Automate the entire process with a SageMaker pipeline Start Date/Time: * North America: July 20th, 9:00 PM PST * Europe/Africa/MiddleEast: July 21st, 5:00 AM BST / 6:00 AM CET * India/Asia/Australia: July 21st, 9:30 AM IST / 12:00 PM Singapore / 2:00 PM Sydney RSVP: https://learn.xnextcon.com/event/eventdetails/W20072021 Agenda: [30 mins] Setup [30 mins] Ingest Data [30 mins] Explore Data [15 mins] Q&A / Break [30 mins] Prepare Data [30 mins] Train Model [30 mins] Q&A / Meal Break [30 mins] Optimize Model [30 mins] Deploy Model [30 mins] Create Pipeline [15 mins] Q&A / Wrap Up Attendees will learn how to: * Ingest data into S3 using Amazon Athena and the Parquet data format Visualize data with pandas, matplotlib on SageMaker notebooks and AWS Data Wrangler * Analyze data with the Deequ library, Apache Spark, and SageMaker Processing Jobs * Perform feature engineering on a raw dataset using Scikit-Learn and SageMaker Processing Jobs * Train a custom BERT model using TensorFlow, Keras, and SageMaker Training Jobs * Find the best hyper-parameters using SageMaker Hyper-Parameter Optimization Service (HPO) * Deploy a model to a REST Inference Endpoint using SageMaker Endpoints * Perform batch inference on a model using SageMaker Batch Transformations * Automate the entire process using StepFunctions, EventBridge, and S3 Triggers Pre-requisites: * Modern browser - and that is it! * Nothing will be installed on your local laptop

Online workshop: Explanations and ML Pipelines - ML in Production

This is online tech event, you can join from anywhere with zoom, please register and attend here: https://learn.xnextcon.com/event/eventdetails/W20070910 We are hosting Free half-day online workshop on Explanations and ML Pipelines - ML in Production. Explanations and ML Pipelines - ML in Production Date: Jul. 23rd, 10am PT/1pm ET RSVP: https://learn.xnextcon.com/event/eventdetails/W20070910 In this workshop, we will cover 2 important aspects of applied machine learning systems - Explanations and Machine Learning Pipelines. We will start with a technical talk on Explainable AI and cover the key methods to generate explanations. After the technical talk, we will conduct a hands on workshop where we will cover how to set up ML data and re-training pipelines. We will cover both streaming and batch updates to data and how ML retraining pipelines can be set up to pick up the latest versions of a dataset. We will finish with generating explanations for models. Agenda (US pacific time, GMT-7): [10:00 - 10:10am] Welcome and workshop overview [10:10 - 10:45am] Explainable AI - overview and science behind the different approaches [10:45 - 11:45am] Hands on workshop [11:45 - 12:00pm] Q&A and wrap up

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