• PipelineAI, KubeFlow, TFX, GPU/TPU, Spark, TensorFlow, Kubernetes, Kafka, Scikit

    Online Workshop - See Details Below

    Title [1 hr Free Workshop] PipelineAI, KubeFlow, TensorFlow Extended (TFX), Airflow, GPU, TPU, Spark ML, TensorFlow AI, Kubernetes, Kafka, Scikit Agenda Hands-on Learning with PipelineAI using KubeFlow, TFX, TensorFlow, GPU/TPU, Kafka, Scikit-Learn and JupyterLab running on Kubernetes. Date/Time 9-10am US Pacific Time (Third Monday of Every Month) ** RSVP & LOGIN HERE ** Eventbrite: https://www.eventbrite.com/e/1-hr-free-workshop-pipelineai-gpu-tpu-spark-ml-tensorflow-ai-kubernetes-kafka-scikit-tickets-45852865154 Meetup: https://www.meetup.com/Advanced-Spark-and-TensorFlow-Meetup/ Zoom: https://zoom.us/j/690414331 Webinar ID:[masked] Phone: [masked] (US Toll) or [masked] (US Toll) Related Links PipelineAI Home: https://pipeline.ai PipelineAI Community Edition: https://community.pipeline.ai PipelineAI GitHub: https://github.com/PipelineAI/pipeline PipelineAI Quick Start: https://quickstart.pipeline.ai Advanced Spark and TensorFlow Meetup (SF-based, Global Reach): https://www.meetup.com/Advanced-Spark-and-TensorFlow-Meetup YouTube Videos: https://youtube.pipeline.ai SlideShare Presentations: https://slideshare.pipeline.ai Slack Support: https://joinslack.pipeline.ai Web Support and Knowledge Base: https://support.pipeline.ai Email Support: [masked]

  • KubeFlow +Keras/TensorFlow 2.0 +TF Extended (TFX) +Kubernetes +Airflow +PyTorch

    Online Workshop - See Details Below

    **Title** Hands-on Learning with KubeFlow + Keras/TensorFlow 2.0 + TF Extended (TFX) + Kubernetes + PyTorch + XGBoost + Airflow + MLflow + Spark + Jupyter + TPU RSVP: https://www.eventbrite.com/e/full-day-workshop-kubeflow-kerastensorflow-20-tf-extended-tfx-kubernetes-pytorch-xgboost-airflow-tickets-63362929227 **Description** In this workshop, we build real-world machine learning pipelines using TensorFlow Extended (TFX), KubeFlow, and Airflow. Described in the 2017 paper, TFX is used internally by thousands of Google data scientists and engineers across every major product line within Google. KubeFlow is a modern, end-to-end pipeline orchestration framework that embraces the latest AI best practices including hyper-parameter tuning, distributed model training, and model tracking. Airflow is the most-widely used pipeline orchestration framework in machine learning. **Pre-requisites** Modern browser - and that's it! Every attendee will receive a cloud instance Nothing will be installed on your local laptop Everything can be downloaded at the end of the workshop **Location** Online **Agenda** 1. Create a Kubernetes cluster 2. Install KubeFlow, Airflow, TFX, and Jupyter 3. Setup ML Training Pipelines with KubeFlow and Airflow 4. Transform Data with TFX Transform 5. Validate Training Data with TFX Data Validation 6. Train Models with Jupyter, Keras/TensorFlow 2.0, PyTorch, XGBoost, and KubeFlow 7. Run a Notebook Directly on Kubernetes Cluster with KubeFlow 8. Analyze Models using TFX Model Analysis and Jupyter 9. Perform Hyper-Parameter Tuning with KubeFlow 10. Select the Best Model using KubeFlow Experiment Tracking 11. Reproduce Model Training with TFX Metadata Store and Pachyderm 12. Deploy the Model to Production with TensorFlow Serving and Istio 13. Save and Download your Workspace **Key Takeaways** Attendees will gain experience training, analyzing, and serving real-world Keras/TensorFlow 2.0 models in production using modern frameworks and open-source tools. RSVP: https://www.eventbrite.com/e/full-day-workshop-kubeflow-kerastensorflow-20-tf-extended-tfx-kubernetes-pytorch-xgboost-airflow-tickets-63362929227

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  • TensorFlow Extended (TFX) + KubeFlow + IBM Open Source AI + Kubernetes + Airflow

    Thanks to IBM Data Science Community for hosting the event at 425 Market street and offering to provide the refreshments Join the IBM Data Science Community https://www.ibm.com/community/datascience/ and participate in shaping the digital future. The talks will be recorded and posted to https://youtube.pipeline.ai Doors Open: 6:00pm Talks Start: 6:30pm Mingle: 8:30pm End: 9:00pm Agenda 1. Intro IBM (5 mins) 2. Meetup Updates and Announcements (5 mins) 3. IBM Open Source AI: How to prepare your AI for the next wave of regulations: Trust and Transparency in ML life cycles (30 mins) Speaker: Sepideh Seifzadeh, PhD (https://www.linkedin.com/in/sepiseif/) In this talk, we demonstrate how to operationalize machine learning algorithms and monitor and manage the deployed models. We also cover how to evaluate the models that have been operationalized in production to track and measure the impact of AI on business outcomes, drive fair outcomes and explain decisions to comply with regulations and govern AI to adapt AI to changing business situation. We also talk about model explainability feature which helps us to better understand why a certain algorithm has come up with certain decisions, and how to detect and mitigate the bias to have fair decisions. 4. KubeFlow + Keras/TensorFlow 2.0 + TF Extended (TFX) + Kubernetes + Airflow + Jupyter (30 mins) Speaker: Chris Fregly, Founder @ PipelineAI (https://linkedin.com/in/cfregly) In this talk, we demonstrate a real-world machine learning pipelines using TensorFlow Extended (TFX), KubeFlow, and Airflow. Described in the 2017 paper, TFX is used internally by thousands of Google data scientists and engineers across every major product line within Google. KubeFlow is a modern, end-to-end pipeline orchestration framework that embraces the latest AI best practices including hyper-parameter tuning, distributed model training, and model tracking. Airflow is the most-widely used pipeline orchestration framework in machine learning.

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  • TensorFlow + Swift + OpenAI's Unsupervised Sentiment, KubeFlow, TFX, Kubernetes

    Online Workshop - See Details Below

    Title TensorFlow + Swift + OpenAI's Unsupervised Sentiment Neuron, KubeFlow, TFX, Kubernetes, Kafka, Airflow, Jupyter, Scikit Agenda 1. TensorFlow + Swift + OpenAI's Unsupervised Sentiment Neuron (45 mins) Speaker: Tanmay Bakshi (https://www.linkedin.com/in/tanmay-bakshi-b15012a1) (More details coming soon...) 2. KubeFlow, TFX, Kubernetes, Kafka, Airflow, Jupyter, Scikit, GPU/TPU, Kafka, Scikit-Learn and JupyterLab (15 mins) (More details coming soon...) Date/Time 9-10am US Pacific Time (Third Monday of Every Month) ** RSVP & LOGIN HERE ** Eventbrite: https://www.eventbrite.com/e/1-hr-free-workshop-pipelineai-gpu-tpu-spark-ml-tensorflow-ai-kubernetes-kafka-scikit-tickets-45852865154 Meetup: https://www.meetup.com/Advanced-Spark-and-TensorFlow-Meetup/ Zoom: https://zoom.us/j/690414331 Webinar ID:[masked] Phone: [masked] (US Toll) or [masked] (US Toll) Related Links PipelineAI Home: https://pipeline.ai PipelineAI Community Edition: https://community.pipeline.ai PipelineAI GitHub: https://github.com/PipelineAI/pipeline PipelineAI Quick Start: https://quickstart.pipeline.ai Advanced Spark and TensorFlow Meetup (SF-based, Global Reach): https://www.meetup.com/Advanced-Spark-and-TensorFlow-Meetup YouTube Videos: https://youtube.pipeline.ai SlideShare Presentations: https://slideshare.pipeline.ai Slack Support: https://joinslack.pipeline.ai Web Support and Knowledge Base: https://support.pipeline.ai Email Support: [masked]

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  • KubeFlow +Keras/TensorFlow 2.0 +TF Extended (TFX) +Kubernetes +Airflow +Jupyter

    Online Workshop - See Details Below

    **Title** Hands-on Learning with KubeFlow + Keras/TensorFlow 2.0 + TF Extended (TFX) + Kubernetes + Airflow + Jupyter RSVP: https://www.eventbrite.com/e/full-day-workshop-kubeflow-kerastensorflow-20-tf-extended-tfx-kubernetes-airflow-jupyter-tickets-62027635327 **Description** In this workshop, we build real-world machine learning pipelines using TensorFlow Extended (TFX), KubeFlow, and Airflow. Described in the 2017 paper, TFX is used internally by thousands of Google data scientists and engineers across every major product line within Google. KubeFlow is a modern, end-to-end pipeline orchestration framework that embraces the latest AI best practices including hyper-parameter tuning, distributed model training, and model tracking. Airflow is the most-widely used pipeline orchestration framework in machine learning. **Pre-requisites** Modern browser - and that's it! Every attendee will receive a cloud instance Nothing will be installed on your local laptop Everything can be downloaded at the end of the workshop **Location** Online The link will be sent a few hours before the start of the workshop. Only registered users will receive the link. If you do not receive the link a few hours before the start of the workshop, please send your Eventbrite registration confirmation to [masked] for help. **Agenda** 1. Create a Kubernetes cluster 2. Install KubeFlow, Airflow, TFX, and Jupyter 3. Setup ML Training Pipelines with KubeFlow and Airflow 4. Transform Data with TFX Transform 5. Validate Training Data with TFX Data Validation 6. Train Models with Jupyter, Keras, and TensorFlow 2.0 7. Run a Notebook Directly on Kubernetes Cluster with KubeFlow Fairing 8. Analyze Models using TFX Model Analysis and Jupyter 9. Perform Hyper-Parameter Tuning with KubeFlow and Katib 10. Select the Best Model using KubeFlow Experiment Tracking 11. Reproduce Model Training with TFX Metadata Store 12. Deploy the Model to Production with TensorFlow Serving and Istio 13. Save and Download your Workspace **Key Takeaways** Attendees will gain experience training, analyzing, and serving real-world Keras/TensorFlow 2.0 models in production using modern frameworks and open-source tools. RSVP: https://www.eventbrite.com/e/full-day-workshop-kubeflow-kerastensorflow-20-tf-extended-tfx-kubernetes-airflow-jupyter-tickets-62027635327

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  • [10% OFF] Zero to Deep Learning 5 day Bootcamp - San Francisco

    San Francisco State University

    Get tickets at: bootcamp.zerotodeeplearning.com 10% discount code: SPARK10OFF Zero to Deep Learning Bootcamp A 5 day full time training that brings you from Zero to Deep Learning® with Keras and Tensorflow 2.0. !!!All code updated to Tensorflow 2.0!!! 5 full days of Knowledge and Skill You’ll get versed in Data Visualization, Machine Learning, and Deep Learning. These are the elements that come together to make driverless cars, to recognize faces, to market products, and to drive big decisions from big data. Why Zero to Deep Learning? If you need to learn the foundations of Machine Learning and Deep Learning comprehensively and quickly, our 5-day Bootcamp is for you. It balances breadth and depth, and delivers you an immersive full-time introduction to cutting-edge ML and DL techniques using Python, Keras and Tensorflow. Who should attend? Software Engineers, Software Engineering Managers, and Data Analysts seeking to upskill in Machine Learning & Deep Learning. Machine Learning with Scikit: • Recognize where to use ML • Select best techniques • Manipulate data with Pandas • Visualize data with Matplotlib • Solve regressions & classifications • Evaluate model performance • Serve models with Flask & Heroku Deep Learning with Keras: • Understand DL fundamentals • Build Fully Connected Neural Networks • Train Convolutional Neural Networks • Design Recurrent Neural Networks • Discover Embeddings • Leverage Dropout & Batch Norm • Use GPUs to train faster Deep Learning with Tensorflow: • Discover why TensorFlow is popular • Turn Keras models into Estimators • Debug models with Eager Execution • Scale to large dataset with Data API • Learn about Core API • Tune performance with Tensorboard • Deploy models using cloud services You will Build: • Predict the price of a house • Detect language of a text • Recognize an object in an image • Classify the sentiment in a sentence • Forecast future energy consumption • Deploy an API that predicts phone location from wifi signal Why attend this Bootcamp • To quickly develop your practical skills in Machine and Deep Learning • You’re stuck with online training and want to develop your practical skills • 5 dedicated days to focus on learning ML and DL • You work in a company where ML and DL is becoming increasingly important, and you need to develop a relevant skill set • You are working in a project, or have an upcoming project which requires ML and DL skills • You are a manager and need a robust understanding of ML and DL to manage your team • Want to access new career opportunities or promotions Lead Instructor Francesco is the author of the Zero to Deep Learning book and founder of Catalit Data Science. He works at the cutting edge of Machine and Deep Learning training. Clients include both startups and Fortune 500s. His experience includes: • Lead Data Science instructor at General Assembly and The Data Incubator • Trainer at conferences including Pybay, ODSC, TDWI, AINext • Chief Data Officer and co-founder at Spire, a YC company that invented the first wearable device tracking breathing • Joint PhD in biophysics at University of Padua and Université de Paris VI What is included in the price? • 5-days in-person training led by Francesco Mosconi, expert ML and DL trainer • Customized hands-on labs developed to maximize your learning • Ability to download your labs at the end of the training • Access to a cloud GPU during the training and for 2-weeks afterwards • Expert advisory on your project between 5-6pm Mon-Thurs of the Bootcamp • Self-directed pre-work program to develop your Python skills (if required) • Live Slack support during the Bootcamp • Membership of the Zero to Deep Learning Slack and Facebook community • One copy of the Zero to Deep Learning book • Breakfast, lunch, all-day refreshments • A really fun 5-days! Prerequisites: 1 year of experience in Python Get tickets at: bootcamp.zerotodeeplearning.com 10% discount code: SPARK10OFF

  • Exploring Data Analytics, Image Recognition w/Spark, Keras/TensorFlow & RedisAI

    This is a FREE 1-day Hands-on workshop event with 3 sessions. Due to unexpected reasons, we could not make the PyTorch session available in time for the event. Our sincere apologies for that. Here is the updated agenda for the event: TECH TALK 1: TITLE: "Principals of Predictive Analytics and the path to Time-Series predictions" SPEAKER: Scott Haines, Principal Software Engineer, Twilio Inc. LinkedIn: https://www.linkedin.com/in/scotthaines/ ABSTRACT: Statistical data mining is a useful art that is often skipped in order to race towards trying to throw ML/DL at a data science problem. However this initial exploration step is actually critical to ensuring that your understanding the important properties that your data can uncover. In this session we will learn how to explore the Kaggle Wine Reviews Dataset. We will be looking for statistical trends in the data, learn how to find and fix missing data issues, and impute values to fill in important gaps. We will then move into using Unsupervised Learning methods to find clusters of similar wines and look at using the Apriori algorithm via spark's FPGrowth model. We will be graphing our findings along the way and having fun looking at wine. PRE-REQUISITES FOR HANDS-ON: Workshop code base: https://github.com/newfront/odsc-east2019-warmup TECH TALK 2: TITLE: "Creating and Deploying Models with Jupyter, Keras/TensorFlow 2.0 & RedisAI" SPEAKER: Chris Fregly, Founder and CEO, PipelineAI, a Real-Time Machine Learning and Artificial Intelligence Startup based in San Francisco. Linkedin: https://linkedin.com/in/cfregly/ ABSTRACT: In this session, you will learn how to create a Tensorflow 2.0 model using Keras in Jupyter Notebooks. You will also learn how to access models and interact with them using RedisAI. TECH TALK 3: Dave Nielsen, Head of Community & Ecosystem Programs at Redis Labs LinkedIn: https://linkedin.com/in/dnielsen/ TITLE: "An Intro to Redis Streams" SPEAKER: Dave Nielsen, Head of Community & Ecosystem Programs at Redis Labs Linkedin: https://linkedin.com/in/dnielsen/ ABSTRACT: In this session, you will learn the basics of Redis Streams. You will also learn how to create and access a Redis Streams Publisher, Chanel and Subscriber. SCHEDULE: 9:30am: Networking 9:45am: Introduction by Arivoli & Dave Nielsen 10:00am-12:30pm: "Principals of Predictive Analytics and the path to Time-Series predictions", by Scott Haines 12:30pm-1:15pm: LUNCH 1:15pm - 2:30pm: "Creating and Deploying Models with Jupyter, Keras/TensorFlow 2.0 & RedisAI", by Chris Fregly 2:30pm - 3:15pm: "An Intro to Redis Streams", by Dave Nielsen VENUE: HackerDojo 3350 Thomas Road, Suite 150 Santa Clara, CA 95054 FOOD SPONSOR: Redis Labs

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  • KubeFlow + AirFlow + TensorFlow Extended (TFX) + TF Encrypted + RedisAI Streams

    Online Workshop - See Details Below

    Title KubeFlow + Airflow + TF 2.0 + TensorFlow Extended (TFX) + TF Encrypted + RedisAI Agenda 1. Redis AI + TensorFlow + PyTorch + Redis Streams Speaker: Dave Nielsen, Head of Community and Ecosystem @ Redis Labs (https://www.linkedin.com/in/dnielsen) 2. TensorFlow Encrypted Machine learning applied to healthcare or otherwise sensitive data may be blocked if privacy isn’t adequately addressed. In this presentation we give an overview of how the TF Encrypted open source library can be used to make predictions and fit models on encrypted data in TensorFlow, without first needing to master advanced cryptography. Speaker: Morten Dahl, Research Scientist @ DropOut Labs (https://www.linkedin.com/in/mortendahlcs) 3. KubeFlow + Airflow + TensorFlow Extended (TFX) Speaker: Chris Fregly, Founder @ PipelineAI (https://www.linkedin.com/in/cfregly) Date/Time 9-10am US Pacific Time (Third Monday of Every Month) ** RSVP & LOGIN HERE ** Eventbrite: https://www.eventbrite.com/e/1-hr-free-workshop-pipelineai-gpu-tpu-spark-ml-tensorflow-ai-kubernetes-kafka-scikit-tickets-45852865154 Meetup: https://www.meetup.com/Advanced-Spark-and-TensorFlow-Meetup/events/jwhkqqyzdbxb/ Zoom: https://zoom.us/j/690414331 Webinar ID:[masked] Phone: [masked] (US Toll) or [masked] (US Toll) Related Links PipelineAI Home: https://pipeline.ai PipelineAI Community Edition: https://community.pipeline.ai PipelineAI GitHub: https://github.com/PipelineAI/pipeline PipelineAI Quick Start: https://quickstart.pipeline.ai Advanced Spark and TensorFlow Meetup (SF-based, Global Reach): https://www.meetup.com/Advanced-Spark-and-TensorFlow-Meetup YouTube Videos: https://youtube.pipeline.ai SlideShare Presentations: https://slideshare.pipeline.ai Slack Support: https://joinslack.pipeline.ai Web Support and Knowledge Base: https://support.pipeline.ai Email Support: [masked]

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  • Latest Keras/TensorFlow 2.0, NLP with Stanford SQuAD, Spark SQL Expressions

    Thanks to Grammarly SF for hosting! The talks will be recorded. Doors Open: 6:00pm Talks Start: 6:30pm Mingle: 8:30pm End: 9:00pm Agenda * Intro Grammarly (Umayah Abdennabi, 5 mins) * Meetup Updates and Announcements (Chris, 5 mins) * Custom Functions in Spark SQL (30 mins) Speaker: Umayah Abdennabi Spark comes with a rich Expression library that can be extended to make custom expressions. We will look into custom expressions and why you would want to use them. * TF 2.0 + Keras (30 mins) Speaker: Francesco Mosconi Tensorflow 2.0 was announced at the March TF Dev Summit, and it brings many changes and upgrades. The most significant change is the inclusion of Keras as the default model building API. In this talk, we'll review the main changes introduced in TF 2.0 and highlight the differences between open source Keras and tf.keras * SQUAD Deep-Dive: Question & Answer with Context (45 mins) Speaker: Brett Koonce (https://quarkworks.co) SQuAD (Stanford Question Answer Dataset) is an NLP challenge based around answering questions by reading Wikipedia articles, designed to be a real-world machine learning benchmark. We will look at several different ways to tackle the SQuAD problem, building up to state of the art approaches in terms of time, complexity, and accuracy. https://rajpurkar.github.io/SQuAD-explorer/ https://dawn.cs.stanford.edu/benchmark/#squad Food and drinks will be provided. The event will be held at Grammarly's office at One Embarcadero Center on the 9th floor. When you arrive at One Embarcadero, take the escalator to the second floor where you will find the lobby and elevators to the office suites. Come on up to the 9th floor (no need to check in at security), and ring the Grammarly doorbell.

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  • [1 hr Free] PipelineAI, GPU, TPU, Spark, TensorFlow, Kubernetes, Kafka, Scikit

    Online Workshop - See Details Below

    Title GPU, TPU Workshop: PipelineAI, Spark, TensorFlow, Kubernetes, Kafka, Scikit-Learn Agenda Hands-on Learning with PipelineAI using GPU-based TensorFlow, GPUs, Kafka, and JupyterLab running on Kubernetes. Date/Time 9-10am US Pacific Time (Third Monday of Every Month) Agenda Hands-on Learning with PipelineAI using GPU-based TensorFlow, GPUs, Kafka, and JupyterLab running on Kubernetes. Brett Koonce, https://quarkworks.co: We will discuss how AlphaFold (https://deepmind.com/blog/alphafold/) uses multiple neural networks and reinforcement learning to build an end to end protein modeling pipeline! ** RSVP & LOGIN HERE ** Eventbrite: https://www.eventbrite.com/e/1-hr-free-workshop-pipelineai-gpu-tpu-spark-ml-tensorflow-ai-kubernetes-kafka-scikit-tickets-45852865154 Meetup: https://www.meetup.com/Advanced-Spark-and-TensorFlow-Meetup/events/jwhkqqyzdbxb/ Zoom: https://zoom.us/j/690414331 Webinar ID:[masked] Phone: [masked] (US Toll) or [masked] (US Toll) Related Links PipelineAI Home: https://pipeline.ai PipelineAI Community Edition: https://community.pipeline.ai PipelineAI GitHub: https://github.com/PipelineAI/pipeline PipelineAI Quick Start: https://quickstart.pipeline.ai Advanced Spark and TensorFlow Meetup (SF-based, Global Reach): https://www.meetup.com/Advanced-Spark-and-TensorFlow-Meetup YouTube Videos: https://youtube.pipeline.ai SlideShare Presentations: https://slideshare.pipeline.ai Slack Support: https://joinslack.pipeline.ai Web Support and Knowledge Base: https://support.pipeline.ai Email Support: [masked]

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