Presentation used in MSP Inspire about Azure ML and Power BI.

1. Azure Machine Learning and
Power BI, Better Together!
ORLANDOGOMES
MICROSOFTMVPDATAPLATFORM
MICROSOFTSTUDENTPARTNER(MSP)
MEDIUM.COM/@_ORLANDOGOMES
LINKEDIN.COM/IN/ORLANDOMARIANO
FACEBOOK.COM/PAGE.ORLANDOGOMES

2. Agenda
 Machine Learning;
 Machine Learning Flow;
 Azure Machine Learning;
 R Language;
 Power BI;
 Referencias;
 Demo.

3. Orlando Gomes
 Brazilian;
 BI Consultant;
 Co-Organizer @Nerdzao;
 Microsoft MVP Data Platform;
 Gold Microsoft Student Partner;
 Graduating 5h Year of Mechatronics Engineering - FIAP;
 Working focused on projects using Microsoft BI Platform
 Loves Pokémon and Soccer

4. Let‘s talk what can be…

5. Machine Learning
"Computer science and statistics subfield that deals with building
and studying systems that can learn from data, rather than just
following explicitly programmed instructions."
-Wikipedia

6. Machine Learning Flow
Define
Objective
Collect
Data
Prepare
Data
Train
Models
Evaluate
Models
Publish
Manage
Integrate

7.  Deploy of machine learning models based in cloud;
 It works in “Blocks”, allowing them to be connected by dragging and dropping;
 Integration with R and Python;
 Browser-based;
 Rapid deployment;
 Connection to other Azure services
-Azure HDInsight (Big Data);
-Azure SQL database;
-Virtual machines.
Azure Machine Learning

8.  Cloud-based environment used to work the entire process of creating and managing the
machine learning model (preparing data, training, testing, deploying, managing and
monitoring);
 Model training initially on local machine (using Azure Machine Learning Python SDK) for later
deployment in Azure, making the execution scalable;
 Integration with Open Source technologies such as PyTorch, TensorFlow and scikit-learn;
 Code-low experience: use of the Visual interface (preview) as a friendly environment for the
deployment of models in the block drag-n-drop model;
 Connection to other Azure data services:
-Azure HDInsight (Big Data);
-Azure SQL Database;
-Virtual Machines.
Azure Machine Learning Services

9. Open Source Language, which allows working with:
 Prediction Algorithms - Linear Regression;
- Classification;
- Clustering;
- Recommendation.
 Data Visualization and Graph Generation;
 Creation of Variables, Vectors and Matrices;
 Table Manipulation (dplyr package).
Linguagem R

10. Power BI
Power BI is a collection of software services, applications and connectors that work together to
transform your unrelated data sources into coherent, visually engaging and interactive
information.

11. Power BI

12. Power BI

13.  Azure Machine Learning Web Site
 http://azure.microsoft.com/en-us/services/machine-learning

 Learning Documentation
 http://azure.microsoft.com/en-us/documentation/services/machine-learning
 Azure Machine Learning FAQ
 http://azure.microsoft.com/en-us/documentation/articles/machine-learning-faq
 Azure Machine Learning Pricing
 http://azure.microsoft.com/en-us/pricing/details/machine-learning/
References

14.  Azure Machine Learning Gallery
 https://gallery.azureml.net
 Azure Machine Learning Blog
 http://blogs.technet.com/b/machinelearning
 Revolution Analytics
 http://www.revolutionanalytics.com
References

15.  Colocando o Azure ML no seu Cotidiano
 https://www.youtube.com/watch?v=CNsH2PKPnWI
 Análise Preditiva com Azure Machine Learning e R
 http://www.livrosdonogare.com.br/produto/analise-preditiva-com-azure-machine-learning-e-r/
References

16. orlando.mariano@studentpartner.com
https://linktr.ee/orlandogomes

17. Thank you! =D

18. Demo

19. Q&A