PinnedPublished inTowards Data ScienceBuilding a Data Science Platform with KubernetesHow Kubernetes — the back-end tool — powers the data science team with end-to-end ML life-cycle from model development to deployment.Jul 11Jul 11
Building a Modern Data ArchitectureThe world has moved from databases, and data warehouses to data lakes, data mesh, and data fabrics.Dec 12, 2023Dec 12, 2023
Published inTowards Data ScienceScikit-learn Pipeline Tutorial with Parameter Tuning and Cross-ValidationIt is often a problem, working on machine learning projects, to apply preprocessing steps on different datasets used for training and…Aug 16, 20211Aug 16, 20211
Published inGeek CultureDeploy to Google App Engine using GitHub Actions (CI/CD)Continuous Integration and Continuous Deployment (CI/CD) is the core thing in MLOps (other being Data Version Control) and we will look at…Jul 8, 20211Jul 8, 20211
Published inGeek CultureData Version Control (DVC) with Google Cloud Storage and Python for MLData Version Control is an upcoming area necessary for faster implementation of machine learning iterations and still track the changes in…Jun 13, 20212Jun 13, 20212
My Tech Stack for Data Science Projectswhy I chose Python and Visual Studio Code for my data science projects…Feb 8, 2021Feb 8, 2021
Published inThe StartupPySpark’s Multi-layer Perceptron Classifier on Iris DatasetBuilding a Neural Net on Iris dataset using PySpark’s Multilayer Perceptron ClassifierFeb 5, 20211Feb 5, 20211
Published inGeek CultureSetting up python environment in macOS using Pyenv and PipenvWe often have a problem when working on different projects in local systemFeb 4, 20212Feb 4, 20212
