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Duration 21 hours
Course Outline
Introduction to Big Data Programming with R (bpdR)
- Configuring your environment to utilize pbdR
- Understanding the scope and available tools within pbdR
- Packages frequently used alongside pbdR for Big Data applications
Message Passing Interface (MPI)
- Leveraging pbdR MPI 5
- Techniques for parallel processing
- Point-to-point communication mechanisms
- Transmitting matrices
- Performing matrix summation
- Implementing collective communication
- Calculating matrix sums using Reduce
- Scatter and Gather operations
- Additional MPI communication methods
Distributed Matrices
- Generating a distributed diagonal matrix
- Computing the SVD of a distributed matrix
- Constructing distributed matrices in a parallel environment
Statistical Applications
- Monte Carlo Integration techniques
- Methods for reading datasets
- Loading data across all processes
- Broadcasting data from a single process
- Reading partitioned data structures
- Executing Distributed Regression
- Performing Distributed Bootstrap analysis
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!.
