Data Mining Tutorial For Beginners || Data Mining with Orange

Data Mining Tutorial For Beginners || Data Mining with Orange
Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. #Data #mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information

Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. #Data #mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for further use. #Data_mining is the analysis step of the “knowledge discovery in databases” process, or KDD.

Orange is an open-source data visualization, machine learning and data mining toolkit. It features a visual programming front-end for explorative rapid qualitative data analysis and interactive data visualization.

⭐️ Table of Contents ⭐️
⌨️ 0:00:00 Welcome to Orange Data mining
⌨️ 0:02:08 Data Workflows
⌨️ 0:04:31 Orange Widgets and channels
⌨️ 0:07:32 Loading your data
⌨️ 0:11:34 Hierarchical clustering
⌨️ 0:15:25 Making prediction
⌨️ 0:18:58 Model evaluation and scoring
⌨️ 0:22:36 Add ons
⌨️ 0:25:17 Principal component analysis
⌨️ 0:28:08 Feature scoring and ranking
⌨️ 0:31:36 K-means
⌨️ 0:35:49 K-means clustering
⌨️ 0:45:10 Image analytics - Clustering
⌨️ 0:48:16 Text preprocessing
⌨️ 0:52:12 Text clustering
⌨️ 0:55:50 Text classification
⌨️ 0:59:45 Importing text documents
⌨️ 1:02:52 Multivariate projection - freeviz
⌨️ 1:06:24 Text processing - documents embeddings
⌨️ 1:10:07 Text mining - document to network
⌨️ 1:13:15 Sentiment analysis
⌨️ 1:17:38 Text mining - twitter data analysis

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