Data scientists develop a functioning model using a machine learning framework and some data. The developed model has a low error rate and a set of hyperparameters optimized. But when…
This article is a guide to plotting regression line in Python. It will focus on linear regression. We will learn the crucial concepts with code in python. Once finished we'll…
This post shows AWS serverless architecture to deploy a machine learning application. I will deploy the food recipe application as discussed here using AWS Fargate. Fargate is a service provided…
This blog post discusses how to quickly save a trained machine learning model that suggests recipes based on the user's data, and nutritional value using Joblib and Pickle. The reason…
This article discusses Machine Learning Model Operationalization Management (MLOps) tools to develop and deploy a food recipe application. It lists the tools that are framework-, platform-, and infrastructure-agnostic using Python…
In this post, we will deploy a serverless machine learning model to AWS using Serverless. The set-up of Serverless is discussed here. Let's create a directory mkdir scikit-regression && cd…
This post details how to develop data-driven analytics support for e-commerce. E-Commerce is a fast-growing and highly competitive space. Businesses need to continue testing and iterating to improve business operations,…
This post provides a link to my Github repository for my submissions for Udacity's AI for Healthcare Nanodegree Program. I learned to build, evaluate, and integrate predictive models that have the power to transform patient outcomes and uses AI for Healthcare. I started by classifying and segmenting 2D and 3D medical images to augment diagnosis and then moved on to modelling patient outcomes with electronic health records to optimize clinical trial testing decisions. Finally, I build an algorithm that uses data collected from wearable devices to estimate the wearer's pulse rate in the presence of motion. Applying AI to 2D Medical Imaging Data…