Build, Train, and Deploy Models with Amazon SageMaker
Learn to build, train, and deploy machine learning models using Amazon SageMaker through hands-on experience. Gain practical skills in ML model development and implementation on AWS platform.
Simplify ML Pipeline Automation and Tracking Using Kubeflow and Serverless Functions
Simplify ML pipeline automation and tracking with Kubeflow and serverless functions. Learn to streamline your machine learning workflows for improved efficiency and productivity.
Introduction to Machine Learning with Python
Explore machine learning fundamentals using Python, covering key concepts and practical applications in this hands-on workshop led by a field engineer from Domino.
Automated Pipeline for Large-Scale Neural Network Training and Inference
Explore cloud-native ML pipeline for automated anomaly detection using BiLSTM models. Learn to manage thousands of models with data collection, training, validation, and deployment techniques.
MLOps at Scale: Predicting Bus Departure Times Using 18,000 ML Models
Explore MLOps at scale through a case study on predicting bus departure times using 18,000 ML models. Learn practical insights for implementing large-scale machine learning projects.
Your First ML Model in Production - Considerations and Examples
Explore strategies for impactful data science projects, from identifying business objectives to deploying ML models in production. Learn real-time scoring, API integration, and lifecycle management with practical examples.
The Algorithm is Not Enough: UX Meets Data Science
Explore the synergy between UX and data science, learning how to integrate user-centric design with data-driven insights for more effective product development.
Serverless for Machine Learning Pipelines
Explore serverless architecture for ML/DL deployment, utilizing AWS services to organize scalable and affordable deep learning workflows for efficient model training and operationalization.
Principles of Good Machine Learning Systems Design
Learn key principles for designing effective machine learning systems, from project scoping to deployment and maintenance, with insights on team structuring and the ML production ecosystem.
Simplifying Machine Learning Lifecycle Management in Healthcare
Explore end-to-end ML lifecycle in healthcare using Azure services. Learn data ingestion, model creation, deployment, and visualization for real-time patient predictions and batch scoring.
Introduction to TensorFlow - Hands-on Workshop
Explore TensorFlow through hands-on practice, completing an end-to-end tutorial to gain practical skills in building and deploying machine learning models.
ML-Based Privacy-Preserving Framework for Generating Synthetic Data from Aggregated Sources
Explore a multi-stage framework for generating synthetic data from aggregated sources, focusing on downscaling techniques and real-world applications in data privacy and model performance improvement.
MLOps Without Much Ops - Building Efficient Machine Learning Systems
Discover modern, no-nonsense data pipelines for efficient machine learning systems. Learn PaaS advantages and explore real-world applications with open-source code. Gain insights on ML's future for organizations of all sizes.
AI and Advanced Analytics in Retail
Explore key ML, DL, RL, and Graph Analytics use cases in Retail, with a demo of Microsoft Azure AI platform's MLOps capabilities in a Retail environment.
Solving for Infrastructure Through the Cloud in Healthcare AI Implementation
Explore cloud-based solutions to overcome AI implementation challenges in healthcare, addressing infrastructure gaps and enabling real-world impact on patient care.
Your First ML Model in Production: Examples and Considerations
Explore strategies for impactful ML projects, from identifying business objectives to deploying models in production. Learn real-time scoring, API integration, and lifecycle management.
Machine Learning Simplified - From Ideation to Deployment in Minutes with Automated ML
Discover how to train high-quality ML models using Azure Machine Learning's automated ML, requiring only a dataset and minimal configuration parameters.
Beginning Your Journey with AI Art
Explore AI art creation using accessible tools and visual programming. Learn dataset manipulation and Cables.gl basics for innovative designs in motion graphics and data visualization.
Speeding Up Innovation with Cloud-Native and Continuous Delivery
Discover modern best practices for accelerating innovation through continuous delivery, cloud-native architecture, and chaos engineering, drawing from global organizational experiences and practical implementations.
Unveiling the Power of IoTDB Stream Processing Engine in Industrial IoT Edge-Cloud Applications
Discover how IoTDB's stream processing engine revolutionizes Industrial IoT with real-time data handling and edge-cloud integration for enhanced operational efficiency.
Data Analysis in VR Games vs Traditional Games - Importance and Applications
Explore how VR gaming leverages data analytics to understand player behavior, create personalized experiences, and overcome unique challenges in immersive virtual environments.