Implementing a data prediction using Azure Machine Learning

Agenda • What is Artificial Intelligence (AI) ? • What are the technologies behind

• MVP AI and Data Platform • Pass Chapter Leader do SQLManiacs •

What is Artificial Intelligence (AI) ? • The theory has existed since 1956; •

What is Artificial Intelligence (AI) ? • Good data models to sort, process and

What are the technologies behind AI? • Machine Learning; • Deep Learning; • Natural

Machine Learning • Involves computers using data to learn with minimal programming; • Allow

Supervised Learning • The machine has a "supervisor" or a "teacher“ who gives the

Supervised Learning Classification • Splits objects based at one of the attributes known beforehand;

Supervised Learning Regression • Regression is basically classification where we forecast a number instead

Deep Learning • Part of machine learning that uses complex algorithms; • Imitate the

Natural language processing (NLP) • Uses machine learning to find patterns in large data

How can AI be used in our daily lives? • Applications such as Siri

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Implementing a data prediction using Azure Machine Learning

Agenda • What is Artificial Intelligence (AI) ? • What are the technologies behind AI? • How can AI be used in our daily lives?

• MVP AI and Data Platform • Pass Chapter Leader do SQLManiacs • Vitor. fava@vitadbsolutions. com Vitor Fava • http: //www. vitadbsolutions. com Principal Database Architect – Vita Database Solutions • http: //vfava. wordpress. com • http: //www. youtube. com/vitortff • Tele. Gram vitortadeu. fava @sqlservermaniac /vitorfava

Artificial Intelligence Expectations

Artificial Intelligence - Reality

What is Artificial Intelligence (AI) ? • The theory has existed since 1956; • Ability of making decisions as human beings; • Computers still need three things to evolve from simple computation to a real AI;

What is Artificial Intelligence (AI) ? • Good data models to sort, process and analyze the data intelligently; • Access to large amounts of raw data; • Processing power (GPU) with affordable cost;

What is Artificial Intelligence (AI) ?

What are the technologies behind AI? • Machine Learning; • Deep Learning; • Natural language processing (NLP);

Machine Learning • Involves computers using data to learn with minimal programming; • Allow the machine to learn rules on its own from the data fed, such as personalized recommendations on Netflix and Amazon; • Machine learning is the main driver of artificial intelligence;

Machine Learning

Supervised Learning • The machine has a "supervisor" or a "teacher“ who gives the machine all the answers • For example, whether it's a cat in the picture or a dog; • The teacher has already divided (labeled) the data into cats and dogs, and the machine is using these examples to learn; • There are two types of such tasks: classification and regression

Supervised Learning Classification • Splits objects based at one of the attributes known beforehand; • – Spam filtering; – A search of similar documents; – Sentiment analysis; – Fraud detection;

Supervised Learning Classification

Supervised Learning Regression • Regression is basically classification where we forecast a number instead of category; • Stock price forecasts; • Demand sales volume analysis; • Any number-time correlations;

Supervised Learning Regression

Deep Learning • Part of machine learning that uses complex algorithms; • Imitate the neural network of the human brain; • Learning an area of knowledge with little or no supervision;

Natural language processing (NLP) • Uses machine learning to find patterns in large data sets and recognize natural language; • Provides the ability to understand compose texts; • Recognize the context, make syntactic, semantic, lexical and morphological analysis, create summaries, extract information, interpret the meanings and analyze feelings;

How can AI be used in our daily lives? • Applications such as Siri and Cortana use voice processing to act as a personal assistant; • Facebook uses image recognition to recommend tagging in photos; • Amazon makes personalized recommendation of products using machine learning algorithms;

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