A Machine Learning Engineer who needs to figure out distributions of features to create better models, or a Platform Engineer who needs to monitor the platform for metrics like requests per minute, needs to draw and understand graphs.
Knowing what graph works in which situation can make it easier to…
Matrix multiplication is the one of the most fundamental operation that most of the machine learning algorithms rely on. Knowing the working of matrix multiplication in a distributed system provides important insights on understanding the cost of our algorithms. Google’s PageRank algorithm is also based on repeated multiplication of matrices…
In How Map Reduce Let You Deal With PetaByte Scale With Ease, an introduction to how map reduce works and what are the reasons for it to be easily scalable were discussed. …
Map Reduce is the core idea used in systems which are used in todays world to analyse and manipulate PetaByte scale datasets (Spark, Hadoop). Knowing about the core concept gives a better understanding of why these systems do certain operations on data at certain stages. Which in turn helps design…
