This talk will provide an overview of typical Data Analysis tools and Machine Learning algorithms, highlighting the arithmetic and data operations that are executed with extreme repetition. Knowing what tools and libraries to use and having a sense of how they work will form the foundation for the next level of discussions around how to profile the use cases and narrow down the optimization techniques to target, including ARM® NEON™, OpenCL(GPU/DSP/other) etc. Python Pandas library was used for Data Analysis. Python sci-kit learn library was used to analyze various Supervised Machine Learning algorithms including K-Nearest Neighbors, Linear & Logistic Regression, Bayesian Classifiers, Decision Trees, Bagging and Random Forests.
Event Date: March 10, 2016