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#Machine Learning Pipelines

Showing: 39 courses
MLOps.community

From Notebook to Kubernetes: Scaling GenAI Pipelines with ZenML

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Explore a lightning talk demonstrating how ZenML, an open-source MLOps framework, facilitates the seamless transition from local development to cloud-scale deployment of generative AI pipelines. Follow a workflow that begins in a Jupyter notebook with lo…
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1 Lesons
13 minutes
On-Demand
Free-Video
MLOps World: Machine Learning in Production

Building Pipelines with Kubeflow - Hands-on Workshop

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Discover Kubeflow pipelines: create environments, build and upload pipelines, and set up retraining schedules in this hands-on workshop for MLOps practitioners.
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1 Lesons
3 hours 43 minutes
On-Demand
Free-Video
MLOps World: Machine Learning in Production

Intro to MLOps: Build, Deploy, and Retrain a Model in Production

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Build, deploy, and retrain a production ML model using open-source tools. Learn robust MLOps pipeline techniques for quick model deployment and continuous improvement.
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1 Lesons
1 hour 1 minute
On-Demand
Free-Video
TensorFlow

TensorFlow Extended - Machine Learning Pipelines and Model Understanding

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Explore TFX for building production-ready ML pipelines. Learn data processing, model analysis, and versioning techniques for large datasets, enhancing your machine learning workflow.
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40 Lesons
38 minutes
On-Demand
Free-Video
TensorFlow

TensorFlow Extended - TFX Overview and Pre-Training Workflow

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Explore TensorFlow Extended's pre-training workflow, focusing on data validation and transformation for robust machine learning pipelines. Learn key components and best practices for efficient ML development.
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31 Lesons
32 minutes
On-Demand
Free-Video
Anyscale

Scaling AI at Autodesk with Ray and Metaflow

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Explore a 15-minute conference talk from Ray Summit 2024 where Thomas Gale and Peter Meltzer from Autodesk, alongside Savin Goyal from Outerbounds, demonstrate how Autodesk leverages Ray and Metaflow for large-scale 3D generative AI operations. Learn abo…
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1 Lesons
15 minutes
On-Demand
Free-Video
Linux Foundation

Lessons Learned From Machine Learning Pipelines in Production

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Explore practical insights on implementing machine learning pipelines in production environments, focusing on challenges, solutions, and best practices using Kedro framework.
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16 Lesons
21 minutes
On-Demand
Free-Video
The Machine Learning Engineer

MLOps MLFlow: Mlflow Projects - Databricks and MLFlow Pipelines

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Aprende a crear pipelines de ejecución con MLflow Projects, utilizando Databricks como repositorio de artefactos y servidor de seguimiento para registrar toda la actividad.
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1 Lesons
20 minutes
On-Demand
Free-Video
The Machine Learning Engineer

MLOps MLFlow: Creating Pipelines with MLflow Projects - Part 1 (Español)

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Aprende a crear pipelines de ejecución con MLflow Projects para optimizar tus flujos de trabajo en ciencia de datos y aprendizaje automático.
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1 Lesons
29 minutes
On-Demand
Free-Video
Open Data Science

Managing Spatiotemporal Data Fusion at Scale Using The Geodesic Platform

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Explore managing large-scale spatiotemporal data fusion using the Geodesic Platform. Learn about cloud-native solutions, data ingest challenges, and leveraging Pachyderm for traceability and pipeline management.
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21 Lesons
34 minutes
On-Demand
Free-Video
Databricks

Data Microservices in Apache Spark Using Apache Arrow Flight

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Explore efficient machine learning pipelines using Apache Arrow Flight in Spark, enabling faster data transport and simplified microservices for improved ML model production.
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11 Lesons
24 minutes
On-Demand
Free-Video
Bryan Cafferky

The Azure Machine Learning Service - Introduction

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Explore Azure ML Service's features for scaling, automating, and deploying machine learning pipelines. Learn how it enhances the data science process and addresses key challenges.
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15 Lesons
52 minutes
On-Demand
Free-Video
Linux Foundation

Building ML Pipelines in JupyterLab Using Elyra - Without Writing Code

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Learn to create ML pipelines visually in JupyterLab with Elyra, exploring pipeline properties, components, runtime environments, and remote execution options.
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15 Lesons
42 minutes
On-Demand
Free-Video
CNCF [Cloud Native Computing Foundation]

Transforming Jupyter Notebooks to Reproducible Machine Learning Pipelines with Kale

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Learn to convert Jupyter notebooks into scalable Kubeflow pipelines using Kale, enabling seamless deployment of ML workflows on Kubernetes for improved reproducibility and efficiency.
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1 Lesons
53 minutes
On-Demand
Free-Video
CNCF [Cloud Native Computing Foundation]

Scheduling Jupyter Notebooks Using Airflow on Kubernetes

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Learn to schedule Jupyter notebooks using Airflow on Kubernetes, enabling scalable data pipelines and machine learning workflows with enhanced security and resource management.
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1 Lesons
28 minutes
On-Demand
Free-Video
OSACon

Building AI Pipelines with Hugging Face and Kedro - From ChatGPT to Production

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Discover how to build robust AI systems using Hugging Face's open models and Kedro pipelines, moving beyond commercial AI to create customizable and transparent machine learning solutions.
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1 Lesons
29 minutes
On-Demand
Free-Video
AI Bites

Optimizing LLM Pipelines with DsPy - Part 2

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Dive into optimizing LLM pipelines by implementing multi-hop question-answering with DsPy framework, featuring Baleen pipeline and Bootstrap Few Shot algorithm optimization techniques.
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7 Lesons
10 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

Towards Observability for Machine Learning Pipelines

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Explore end-to-end observability for ML pipelines. Learn about a system that enhances visibility, executes tests, tracks data flow, and enables post-hoc analysis of pipeline health.
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1 Lesons
1 hour 22 minutes
On-Demand
Free-Video
Prodramp

A Visual Introduction to Modern and Scalable Machine Learning Pipeline

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Visual guide to modern, scalable machine learning pipelines: from data prep to deployment. Covers key stages like training, validation, inference, feature stores, and model registry. Ideal for understanding ML infrastructure evolution.
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12 Lesons
20 minutes
On-Demand
Free-Video
IEEE

Defense Against the Dark Arts

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Overview of adversarial example research in machine learning, exploring attacks, defenses, and future directions for enhancing AI security and robustness against malicious inputs.
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15 Lesons
57 minutes
On-Demand
Free-Video
Open Data Science

Building Real-Time ML Pipelines the Easy Way

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Learn to build real-time ML pipelines for fraud prediction, predictive maintenance, and customer churn prevention. Explore challenges, solutions, and best practices for handling high-velocity data and triggering actions in seconds.
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16 Lesons
43 minutes
On-Demand
Free-Video
Databricks

MATS Stack for Cross-System Orchestration of Machine Learning Pipelines

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Explore the MATS stack for orchestrating ML pipelines across systems, featuring MLFlow, Airflow, Tensorflow, and Spark. Learn how Avast leverages this approach for efficient phishing detection and streamlined ML workflows.
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7 Lesons
22 minutes
On-Demand
Free-Video
Linux Foundation

Writing Machine Learning Pipelines Against Object Storage

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Learn to create efficient machine learning pipelines using object storage, optimizing data processing and model deployment for scalable AI solutions.
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1 Lesons
35 minutes
On-Demand
Free-Video
Linux Foundation

Enforcing Data Quality in Data Processing and ML Pipelines with Flyte and Pandera

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Learn to enforce data quality in processing and ML pipelines using Flyte and Pandera, enhancing reliability and efficiency in data-driven projects.
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1 Lesons
47 minutes
On-Demand
Free-Video
Linux Foundation

Democratization of ML Pipelines and Bringing ML Workflows to Heterogeneous Cloud Native Platforms

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Explore advancements in ML pipeline portability using Intermediate Representation, enabling cross-platform compatibility and democratizing ML workflow development with enhanced features and registry protocols.
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1 Lesons
36 minutes
On-Demand
Free-Video
Linux Foundation

Deploy and Monitor ML Pipelines with Open Source and Free Applications

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Learn to deploy and monitor ML pipelines using open-source tools. Automate data refresh, generate forecasts, and set up monitoring dashboards with GitHub Actions, Docker, MLflow, and more.
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1 Lesons
45 minutes
On-Demand
Free-Video
The Machine Learning Engineer

MLOps MLFlow: Building Pipelines with MLflow Projects

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Build MLflow project pipelines for efficient machine learning workflows. Learn to create and execute data science pipelines using MLflow Projects.
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1 Lesons
33 minutes
On-Demand
Free-Video
Red Hat Developer

Computer Vision Workshop on OpenShift: AI/ML Platform for Model Development and Deployment

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Explore computer vision use cases on OpenShift, from data collection and annotation to model training and deployment, with practical demonstrations on cars and trains detection.
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14 Lesons
18 minutes
On-Demand
Free-Video
CNCF [Cloud Native Computing Foundation]

Scaling ML Pipelines with KALE - The Kubeflow Automated Pipeline Engine

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Discover KALE, the Kubeflow Automated Pipeline Engine, for scaling ML pipelines. Learn how to transform Jupyter Notebook experiments into production-grade pipelines for efficient model training and real-time serving.
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1 Lesons
25 minutes
On-Demand
Free-Video
GOTO Conferences

Production Model Deployment

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Explore strategies for deploying production models, including data sharing, service building, and AB testing. Learn about ML pipelines, engineering requirements, and effective handoff between data scientists and software engineers.
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39 Lesons
46 minutes
On-Demand
Free-Video
PyCon US

Reproducible and Maintainable Data Science Code with Kedro

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Discover how Kedro, an open-source Python framework, transforms experimental data science code into production-ready ML pipelines, emphasizing reproducibility, maintainability, and modularity.
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1 Lesons
26 minutes
On-Demand
Free-Video
EuroPython Conference

Auto-Sklearn - Automated Machine Learning in Python

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Discover Auto-sklearn, an open-source AutoML tool that simplifies machine learning pipeline development. Learn its functionality, benefits, and how to implement it as a scikit-learn replacement.
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1 Lesons
45 minutes
On-Demand
Free-Video
EuroPython Conference

We Build a ML Pipeline After We Deploy

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Discover essential strategies for building end-to-end machine learning pipelines, covering automation, engineering, debugging, and monitoring using Python libraries.
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21 Lesons
32 minutes
On-Demand
Free-Video
EuroPython Conference

The State of Production Machine Learning in 2023

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Explore challenges and solutions in production machine learning, focusing on reliability and scalability. Learn key concepts and recommended tools to tackle the increasing complexity of ML pipelines.
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1 Lesons
45 minutes
On-Demand
Free-Video
CNCF [Cloud Native Computing Foundation]

Machine Learning Pipelines con K3s y Argo

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Aprende a implementar pipelines de Machine Learning utilizando K3s y Argo, optimizando el flujo de trabajo en entornos cloud-native.
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1 Lesons
38 minutes
On-Demand
Free-Video
The Machine Learning Engineer

MLOps with MLflow - Creating Execution Pipelines Using Projects and Databricks

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Explore MLflow Projects to create execution pipelines locally and leverage Databricks for tracking and artifact storage in machine learning workflows.
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1 Lesons
18 minutes
On-Demand
Free-Video
TensorFlow

TFX- Production ML Pipelines with TensorFlow

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Explore TensorFlow Extended (TFX) for production ML pipelines, covering components, metadata storage, orchestration, and custom implementations for scalable and maintainable machine learning solutions.
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22 Lesons
42 minutes
On-Demand
Free-Video
The Machine Learning Engineer

Azure ML: Pipelines with Python SDK for Data Science and Machine Learning

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Create ML pipelines with Azure Machine Learning Studio's Python SDK for efficient data science and machine learning workflows on Azure.
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1 Lesons
57 minutes
On-Demand
Free-Video
Canonical Ubuntu

Building Machine Learning Pipelines with Kubeflow

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Master building ML pipelines using Kubeflow's components, from key considerations to best practices, and learn effective implementation strategies for scaling machine learning projects.
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1 Lesons
52 minutes
On-Demand
Free-Video