Part 2: Machine learning model deployment on Microsoft Azure

Read Time: 3 min In previous post, we learned to design machine learning model on Azure notebook, how to create workspace on Azure and how to register trained model on cloud. “Part 2: Machine learning model deployment on Microsoft Azure ” is continuation of part 1, where we will learn how to deploy the model on Azure container instance. … Read more

Build ML model using Microsoft Azure: Part 1

Read Time: 4 min You might have worked on various data processing techniques, machine learning algorithms from understanding the business requirement, building the machine learning model to model’s validation process. Through this series, we are going to learn how to build ML model from scratch using Microsoft Azure Services i.e. on cloud for fraud detection. In part-1 of this … Read more

Techniques to handle class imbalance

Read Time: 6 min In following post I have explained class imbalance problem in classification models and techniques to handle class imbalance problem using python. Table of content What is the class imbalance? Why class imbalance is an issue? How to handle class imbalance (methods) Use case study with fraud detection data At first we need to understand what … Read more

Part 6: Feature Detection Algorithms (Harris corner detection, FAST, BRIEF, ORB)

Read Time: 5 min In previous posts, we have discussed different image pre-processing techniques through different operations using openCV. This post includes next step towards image processing i.e. feature detection algorithm and feature matching using SIFT (Scale invariant feature transform) and SURF (Speeded-up Robust Features) algorithms and their application using openCV. Here are the links for image processing techniques … Read more

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