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- Data Analytics is defined as the process of investigation of datasets to pull out the conclusions about the information they contain.
- Data analytic is a method to enable you to take raw data and expose design to get valuable comprehension from it.
- Data Analytics give ideas to individuals and organizations for making sense of data.
- They use many different tools and methods that helps organizations to make decisions and succeed.
Types of Data Analytics:
- Descriptive data analytics
- Diagnostic data analytics
- Predictive data analytics
- Prescriptive data analytics
- Statistical analysis tools.
- General-purpose programming languages.
- Standalone predictive analytics tools
- Data modeling tools
- ETL tools
- SQL consoles
From this book you will learn these topics in detail:
- Data science with their relationship
- Data science workflow
- A plot generated by matplotliblity
- How to measure the distance between points A and B
- The curse of dimensionality
- Data Clustering
- Algorithms and applications
- Data Mining
- Data mining in marketing
- Data Science and Analytics With Python
- Healthcare data analytics
- Technologies for Web applications
- Machine learning engineering system and health management
- Music Data mining
- Data Mining use cases with business analytics applications
- Relational data clustering
- Vector machines
- Text mining classifications
- Clustering and applications of text mining
- Visualization of text mining
- Algorithm of text mining