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Related lectures (74)
Parallel Scan Left
Introduces parallel scan left in Scala, covering its properties, sequential solutions, and efficient parallel computation techniques.
Big Data Challenges: Distributed Computing with Spark
Explores big data challenges, distributed computing with Spark, RDDs, hardware requirements, MapReduce, transformations, and Spark DataFrames.
Measurable Functions: Independence
Explores independence between sigma-algebras and measurable functions, emphasizing countably additive measures and their role in defining independence.
Scheduling: Under the Hood
Explores the complexities of scheduling in distributed computing frameworks, emphasizing data locality optimization and multitenancy strategies.
MapReduce: Execution Models for Distributed Computing
Introduces the MapReduce programming model for distributed computing, focusing on its vision and under-the-hood mechanisms.
Google Earth Engine: A Powerful Geospatial Analysis Platform
Introduces Google Earth Engine, a cloud-based platform for planetary scale geospatial analysis, explaining its history, core concepts, and real-life applications.
Data Wrangling with Hadoop: Advanced Techniques
Covers advanced data wrangling techniques using Hadoop, focusing on Hive and HBase integration.
Spatial Statistics: Significance
Explains the calculation of statistical significance in spatial statistics using permutation and randomization methods.
Other Collections: Vectors and Sequences
Covers alternative sequence implementation in Scala, focusing on Vectors and their operations.
Convergent Beam Electron Diffraction
Explores Convergent Beam Electron Diffraction (CBED) for detailed crystal structure information and sample thickness measurement.