Resources aka msAIML 40 repo aka ms9 Tips
- Slides: 44
Resources aka. ms/AIML 40 repo aka. ms/9 Tips. Prod. ML aka. ms/mymsignitethetour
Recap Machine Learning Applications Autonomous Agents Predictive Maintenance Forecasting Language Understanding E-commerce Recommendations Computer Vision
Let’s Dive Deeper: Trends In Language Understanding Ambient Computing Unlocking Unstructured Data Language Understanding Automation and Solution Scale
The Story Existing pre-built models for text analytics Custom models trained on specific data
Demo Text Analytics
/Docs alert Get started with Azure Cognitive Services Text Analytics API aka. ms/Text. Cog. Svc
From Cognitive Services to Azure Machine Learning
What is Azure Machine Learning Service? Set of Azure Cloud Services Python SDK That enables you to: ü Prepare Data ü Build Models ü Train Models ü Manage Models ü Track Experiments ü Deploy Models
Azure ML Service Key Artifacts Workspace
Building a Baseline with Auto. ML Input Azure Auto ML Intelligently test multiple models in parallel Optimized model Enter data Define goals Apply constraints
Demo From Text Analytics to Auto ML
/Docs alert Get started with Automated Machine Learning https: //aka. ms/Automated. MLDoc
Advanced Azure ML Services
NLP-Architect Aspect Based Sentiment Analysis
Azure Machine Learning Typical E 2 E Process Experiment Prepare Deploy … Orchestrate
Azure Machine Learning Typical E 2 E Process Experiment Prepare Deploy … Orchestrate
Managing Tailwind Traders ML Challenges
Challenges of distributed training Dependencies and Containers Handle failures Schedule jobs Secure Access Distribute data Gather results Scale resources Provision clusters of VMs
Features of Distributed Training Horovod distributed training with
/Docs alert Get Started by setting up your Azure ML Environment https: //aka. ms/amlsdk
Distributed Hyperparameter Tuning
What are Hyperparameters? Config 1= {“learning_rate”: 0. 2, “num_layers”: 2, …} { “learning_rate”: uniform(0, 1), “num_layers”: choice(2, 4, 8) … } Config 2= {“learning_rate”: 0. 5, “num_layers”: 4, …} Config 3= {“learning_rate”: 0. 9, “num_layers”: 8, …} …
Typical ‘manual’ approach to hyperparameter tuning Dataset Training Algorithm 1 Algorithm 2 Hyperparameter Values – config 1 Values – config 2 Hyperparameter Values – config 3 Values – config 4 Model Training Infrastructure Complex Tedious Repetitive Time consuming Expensive Model 1 Model 2 Model 3 Model 4
Automated Hyperparameter Tuning Manage Active Jobs Evaluate training runs for specified primary metric Early terminate poor performing training runs. Early termination policies include: Early terminate poorly performing runs
/Docs alert Get started with Azure Machine Learning Service Hyperparameter Tuning https: //aka. ms/Azure. MLHyper. Drive
How Azure ML Workspace Docker Image Compute Target My Computer Data Store
The 8 Azure ML Train Steps
Demo: Operationalizing Open Source with Azure ML and NLP Architect
Wrapping Up
Review
Takeaways
/Docs alert Train an image classification model with MNIST data and Scikit-learn https: //aka. ms/Azure. MLTrain
/Docs alert Getting Started Series… https: //aka. ms/Text. Cog. Svc https: //aka. ms/Automated. MLDoc https: //aka. ms/Azure. MLHyper. Drive https: //aka. ms/AA 3 dzht Other Materials Azure ML Best Practices Repos github. com/microsoft/nlp-recipes/ • Computer Vision github. com/microsoft/Computer. Vision • Recommenders github. com/microsoft/Recommenders https: //aka. ms/9 MLTips
/MS Learn alert aka. ms/AIML 40 MSLearn. Collection
/Microsoft Certification alert aka. ms/Data. Scientist. Cert aka. ms/Data. Engineer. Cert Get hired, stay ahead, and receive the recognition you deserve #MSIgnite. The. Tour
Resources Get Certified aka. ms/AIML 40 repo Azure Data Scientist: aka. ms/Data. Scientist. Cert Azure Data Engineer Associate: aka. ms/Data. Engineer. Cert aka. ms/mymsignitethetour #MSIgnite. The. Tour
Microsoft. com/Certifications Microsoft. com/Learn aka. ms/Learning. Partner
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