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Course Outline
Introduction to Programming Big Data with R (bpdR)
- Configuring your environment for pbdR
- Overview of pbdR's scope and available tools
- Commonly used packages alongside pbdR for Big Data applications
Message Passing Interface (MPI)
- Implementing pbdR MPI 5
- Parallel processing techniques
- Point-to-point communication
- Transmitting matrices
- Summing matrices
- Collective communication strategies
- Summing matrices using Reduce operations
- Scatter and Gather operations
- Additional MPI communication methods
Distributed Matrices
- Constructing a distributed diagonal matrix
- Performing SVD on distributed matrices
- Building distributed matrices in parallel
Statistical Applications
- Monte Carlo Integration
- Reading datasets
- Accessing data across all processes
- Broadcasting data from a single process
- Processing partitioned data
- Distributed regression analysis
- Distributed bootstrap methods
21 Hours
Testimonials (2)
The subject matter and the pace were perfect.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize the training meeting clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!.
