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Exam Description: It is well known that 070-774 exam test is the hot exam of Microsoft MCSA-Machine Learning 070-774 (Perform Cloud Data Science with Azure Machine Learning). IT-Tests.com offer you all the Q&A of the 070-774 Tests . It is the examination of the perfect combination and it will help you pass 070-774 exam at the first time!
Perform Cloud Data Science with Azure Machine learning 70-774 Dumps will include below mentioned topics with Exam focused percentage
- Use Other Services for Machine Learning: 20-25%
- Operationalize and Manage Azure Machine Learning Services: 20-25%
- Develop Machine Learning Models: 20-25%
- Prepare Data for Analysis in Azure Machine Learning and Export from Azure Machine Learning: 20-25%
Reference: https://www.microsoft.com/en-us/learning/exam-70-774.aspx
Microsoft MCSA-Machine Learning 070-774 Perform Cloud Data Science with Azure Machine Learning Exams
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Analyzing Big Data with Microsoft R 70-773 Dumps Provided Study Notes
It-Tests expert team recommend you to prepare some notes on these topics along with it don't forget to practice Perform Cloud Data Science with Azure Machine Learning 70-774 Dumps which been written by our expert team, Both these will help you a lot to clear this exam with good marks.
- Microsoft R Servers.
- HDinsights
- Azure Machine Learning.
- Python Languages.
- Machine Learning Projects and workspace
- Cognitive Services/API
- Data Science
- Algorithms for grouping unlabeled Data.
- SQL/T-SQL
- Machine Learning models
For more info visit:
MICROSOFT 70-774 Exam Reference, Microsoft Documents
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Microsoft 070-774 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Operationalize and Manage Azure Machine Learning Services | - Consume ML models - Deploy models using Azure ML - Manage ML projects and workspaces - Consume related Cognitive Services APIs |
| Prepare Data for Analysis in Azure Machine Learning | - Explore and summarize data - Cleanse data for Azure ML - Import and export data to/from Azure ML - Perform feature engineering |
| Develop Machine Learning Models | - Initialize and train models - Validate models - Select appropriate algorithm/method |
| Use Other Services for Machine Learning | - Build/use neural networks (Microsoft Cognitive Toolkit) - Streamline development with existing resources - Perform data sciences at scale via HDInsight - Perform database analytics using SQL Server R Services |
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