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Oracle data mining tutorial video


Do you want to learn data mining techniques?
Do you want to know how to use Oracle Data Miner?

Watch data mining tutorial and learn how to analyze data and find useful information in large data sets. 8 lessons, total length 2 h 19 min

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Data mining (data discovery, knowledge discovery) is a relatively young and interdisciplinary area of computer science. It is a process that results in the discovery of new patterns in large data sets. It involves analyzing data and finding hidden patterns using automatic means.
At present, more and more data are being collected and saved in databases. Finding useful information in these databases has become an important focus of many companies, and more attention has turned to data mining as a key component to such information discovery.

Data discovery is a relatively young area compared to databases. Although it is still considered a niche and emerging market, knowledge discovery is getting more and more attention in today’s business organizations with a strong consumer focus.

So, what benefits will using data mining techniques bring you?

Data discovery is a powerful technology with great potential. It helps analysts focus on the most important information about the behavior of their customers and potential customers in the data they have collected. It enables companies to determine relationships among various factors such as price, product positioning, customer demographics, economic indicators or competition. Moreover, it discovers information within the data that queries and reports can’t effectively reveal. Data mining is a key member in the warehouse and business intelligence product family.

Oracle Data Mining (ODM) is an option of Oracle Database Management System and provides powerful data mining functionality as native SQL functions. Oracle Data Miner is a graphical user interface for ODM. It is an extension to Oracle SQL Developer that enables to work directly with data inside the database and explore the data graphically.

  1. Data mining fundamentals, setting up Oracle Data Miner (11:35)
    What is data mining, data mining definition, data mining models, data mining algorithms, create a data miner user account, create connection for the data miner user, install repository
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  2. Classification (33:45)
    What is classification, classification definition, create connection, create project, create workflow, classification node, create classification model, algorithm settings, build model, compare the models, performance tab, performance matrix tab, ROC curve, decision tree
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  3. Star schema mining (17:55)
    Aggregate data, data source node, aggregate node, join data sources, create data or view, output node, apply the model, apply node, training data set, testing data set
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  4. Text mining (19:00)
    What is text mining, create text mining model, build text node, apply text node, text transform, tokens, text classification, build, apply and test models
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  5. Data transformation (18:05)
    Data exploration,explore data node , filtering, filter column node, filter rows node, automatic data preparation, binning, discretization, normalization, outlier treatment, attribute importance
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  6. Regression (07:55)
    What is regression, regression definition, create regression model, classification vs regression, residual plot
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  7. Clustering (13:55)
    What is clustering, clustering definition, grouping, K-means algorithm, O-Cluster algorithm, centroid, clusters comparing
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  8. Association rules (16:25)
    What is association, association definition, market basket analysis, transaction, length of the rule, support for the rule, confidence for the rule, lift, joining tables, antecedant, consequent, filtering rules, sorting rules, itemsets
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Price 39.00 USD

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