In this course, you will learn:
- MapReduce knowledge and application.
- Understanding the frequency of event occurrences in huge data.
- In Big Data, how to develop algorithms for stream processing and counting frequent components.
- PageRank algorithms must be understood and designed.
- Recognize the random walk methods that underpin them.
- The basics of working with big data
- Web and social networks
- Clustering big data
- Google web search
- Parallel and distributed computing using MapReduce
- Computing similar documents in big data
- Products frequently bought together in stores
- Movie and music recommendations
- Google's AdWordsTM System
- Mining rapidly arriving data streams