What we're about

This meetup focused on everything KubeFlow AI related including Jupyter Notebooks, Kubernetes, TensorFlow, PyTorch, XGBoost, Scikit-Learn, Deep Learning, Machine Learning, and Artificial Intelligence.

Upcoming events (4)

Kubeflow +Keras/TensorFlow +TFX +Kubernetes +Airflow +PyTorch +SageMaker

**Title** Hands-on Learning with KubeFlow + Keras/TensorFlow 2.0 + TF Extended (TFX) + Kubernetes + SageMaker + 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** 0. Introduction to Kubeflow and SageMaker 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. Deploy the Model to Production with TensorFlow Serving and Istio 12. 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. Related Links Meetup: https://meetup.com/Advanced-Kubeflow/ GitHub Repo: https://github.com/PipelineAI/ O'Reilly Book: https://datascienceonaws.com YouTube: https://youtube.pipeline.ai Slideshare: https://slideshare.pipeline.ai Support: https://support.pipeline.ai Monthly Webinar: https://www.eventbrite.com/e/webinar-pipelineai-kubeflow-tensorflow-extended-tfx-airflow-gpu-tpu-spark-ml-tensorflow-ai-tickets-45852865154 RSVP: https://www.eventbrite.com/e/full-day-workshop-kubeflow-kerastensorflow-20-tf-extended-tfx-kubernetes-pytorch-xgboost-airflow-tickets-63362929227

Kubeflow +Keras/TensorFlow +TFX +Kubernetes +Airflow +PyTorch +SageMaker

**Title** Hands-on Learning with KubeFlow + Keras/TensorFlow 2.0 + TF Extended (TFX) + Kubernetes + SageMaker + 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** 0. Introduction to Kubeflow and SageMaker 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. Deploy the Model to Production with TensorFlow Serving and Istio 12. 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. Related Links Meetup: https://meetup.com/Advanced-Kubeflow/ GitHub Repo: https://github.com/PipelineAI/ O'Reilly Book: https://datascienceonaws.com YouTube: https://youtube.pipeline.ai Slideshare: https://slideshare.pipeline.ai Support: https://support.pipeline.ai Monthly Webinar: https://www.eventbrite.com/e/webinar-pipelineai-kubeflow-tensorflow-extended-tfx-airflow-gpu-tpu-spark-ml-tensorflow-ai-tickets-45852865154 RSVP: https://www.eventbrite.com/e/full-day-workshop-kubeflow-kerastensorflow-20-tf-extended-tfx-kubernetes-pytorch-xgboost-airflow-tickets-63362929227

Kubeflow +Keras/TensorFlow +TFX +Kubernetes +Airflow +PyTorch +SageMaker

**Title** Hands-on Learning with KubeFlow + Keras/TensorFlow 2.0 + TF Extended (TFX) + Kubernetes + SageMaker + 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** 0. Introduction to Kubeflow and SageMaker 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. Deploy the Model to Production with TensorFlow Serving and Istio 12. 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. Related Links Meetup: https://meetup.com/Advanced-Kubeflow/ GitHub Repo: https://github.com/PipelineAI/ O'Reilly Book: https://datascienceonaws.com YouTube: https://youtube.pipeline.ai Slideshare: https://slideshare.pipeline.ai Support: https://support.pipeline.ai Monthly Webinar: https://www.eventbrite.com/e/webinar-pipelineai-kubeflow-tensorflow-extended-tfx-airflow-gpu-tpu-spark-ml-tensorflow-ai-tickets-45852865154 RSVP: https://www.eventbrite.com/e/full-day-workshop-kubeflow-kerastensorflow-20-tf-extended-tfx-kubernetes-pytorch-xgboost-airflow-tickets-63362929227

Kubeflow +Keras/TensorFlow +TFX +Kubernetes +Airflow +PyTorch +SageMaker

**Title** Hands-on Learning with KubeFlow + Keras/TensorFlow 2.0 + TF Extended (TFX) + Kubernetes + SageMaker + 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** 0. Introduction to Kubeflow and SageMaker 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. Deploy the Model to Production with TensorFlow Serving and Istio 12. 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. Related Links Meetup: https://meetup.com/Advanced-Kubeflow/ GitHub Repo: https://github.com/PipelineAI/ O'Reilly Book: https://datascienceonaws.com YouTube: https://youtube.pipeline.ai Slideshare: https://slideshare.pipeline.ai Support: https://support.pipeline.ai Monthly Webinar: https://www.eventbrite.com/e/webinar-pipelineai-kubeflow-tensorflow-extended-tfx-airflow-gpu-tpu-spark-ml-tensorflow-ai-tickets-45852865154 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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