Data Analysis & Visualization for GTU University (VI- CSE/IT/Open Elec.-II - 3161613)  (Paperback, Avinash Jha, Manthan Jayantbhai Surti)

1. Math, probability and statistical modeling Exploring probability and inferential statistics, quantifying correlation, Reducing Data Dimensionality with linear algebra, Modeling Decisions with Multi Criteria Decision making, Regression Methods, Detecting outliers, Time-series analysis. (Chapter - 1) 2. Using Clustering to subdivide data Introducing clustering basics, identifying clusters, Categorizing data with Random forest algorithm. (Chapter - 2) 3. Modeling instances Recognizing the Difference between Clustering and Classification, Making sense of data with nearest neighbor analysis, classifying data with average nearest neighbor algorithms, classifying data with K- nearest neighbor algorithms, Solving Real-world problems. (Chapter - 3) 4. Principles of Data Visualization Design Data visualization : The big three, Designing to meet the needs, Picking the most appropriate Design style, Choosing how to add context, Selecting the appropriate Data Graphic Type, Choosing a Data Graphic, Using D3.js for Data Visualization. (Chapter - 4) 5. Web based applications for visualization design, Exploring best practices in Dashboard Design, Making maps from spatial data. (Chapter - 5) 6. Data science for driving growth in E-commerce. (Chapter - 6)