Overview Learn how to use Shapley values in game theory for machine learning interpretability It’s a unique and different perspective to interpret black-box machine …
Overview Mask R-CNN is a state-of-the-art framework for Image Segmentation tasks We will learn how Mask R-CNN works in a step-by-step manner We will …
A summary of fast.ai’s course that interprets the results of a random forest model using various techniques like partial dependence & tree interpreters.
This article provides a comprehensive summary of fast.ai’s machine learning course. It’s a deep dive into the inner workings of the Random Forest algorithm!
This hands-on guide covers how you can perform automated feature engineering in Python using the open source library Featuretools.
This article introduces you to one of the most common machine learning techniques called K-Nearest Neighbor, along with an implementation in Python.
Dask is a parallel computing python library that can run across a cluster of machines. This article includes a look at Dask Array, Dask Dataframe & Dask ML.
Introduction As a beginner in the world of data science, the first algorithm I was introduced to was Linear Regression. I applied it to …
Note: This article was originally published on August 10, 2015 and updated on Sept 9th, 2017 Overview Major focus on commonly used machine learning …
Introduction Neural network is an information-processing machine and can be viewed as analogous to human nervous system. Just like human nervous system, which is …
