Today, there are scores of databases available in the industry that are marketed as NoSQL systems capable of running complex analytical queries. Most of them have one or more features of typical NoSQL systems, such as columnar, in-memory, key-value, document-oriented, graph-based, and so on. The next section highlights some of the key enterprise NoSQL systems in use today.
- Preface
- Too Big or Not Too Big
- Big Data Mining for the Masses
- The Analytics Toolkit
- Big Data With Hadoop
- Big Data Mining with NoSQL
- Spark for Big Data Analytics
- An Introduction to Machine Learning Concepts
- What is machine learning?
- Factors that led to the success of machine learning
- Machine learning, statistics, and AI
- Categories of machine learning
- Subdividing supervised machine learning
- Common terminologies in machine learning
- The core concepts in machine learning
- Leveraging multicore processing in the model
- Summary
- Machine Learning Deep Dive
- Enterprise Data Science
- Enterprise data science overview
- A roadmap to enterprise analytics success
- Data science solutions in the enterprise
- Enterprise data science – machine learning and AI
- Enterprise infrastructure solutions
- Tutorial – using RStudio in the cloud
- Summary
- Closing Thoughts on Big Data
- External Data Science Resources
- Other Books You May Enjoy
Enterprise data warehouse and data mining
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.