Ratan Gulati @ratanstwt

MERN Developer | Aspiring Software Developer | Building projects & learning in public | #Cloud and #DevOps enthusiast bento.me/ratangulati Joined October 2022

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Ratan Gulati @ratanstwt

a month ago

🚀Day 14 of #MLOps: Logistic Regression! 📦What I explored today: ➡️Logistic Regression – In-depth Math Intuition – sigmoid function, decision boundaries, and log-odds ➡️Explored One-vs-Rest (OVR) strategy for multi-class classification Will be doing the implementation tomorrow

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Ratan Gulati @ratanstwt

a month ago

🚀Day 13 of #MLOps 📦What I explored today: ➡️EDA & Feature Engineering – created meaningful features, encoded variables, transformed skewed data ➡️Feature Selection – reduced noise, focused on the most impactful variable Will work on logistic regression tomorrow.

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Ratan Gulati @ratanstwt

a month ago

🚀 Day 12 of #MLOps: Regularization & Validation 📦 What I explored today: ➡️ Learned the core ideas behind Ridge Regression – penalizing large coefficients to reduce variance ➡️ Explored Lasso & ElasticNet – balancing feature selection and shrinkage in one go Let's gooo!

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Ratan Gulati @ratanstwt

a month ago

🚀 Day 11 of #MLOps: Polynomial Regression 📦 What I explored today: ➡️Understood the intuition behind Polynomial Regression – capturing curves in data ➡️Implemented Polynomial Regression from scratch – built models that bend and adapt Will start Ridge and Lasso tomorrow.

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Ratan Gulati @ratanstwt

a month ago

🚀 Day 11 of #MLOps: Polynomial Regression 📦What I explored today: ➡️Understood the intuition behind Polynomial Regression – capturing curves in data ➡️Implemented Polynomial Regression from scratch – built models that bend and adapt Will start Ridge and Lasso tomorrow.

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 10 of #MLOps: Linear Regression 📦What I explored today: ➡️Revisited Multiple Linear Regression for multi-feature modeling ➡️Learned about Performance Metrics – how to measure predictions ➡️Broke down MSE, MAE, RMSE – when to use what and why

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 10 of #MLOps: Linear Regression 📦 What I explored today: ➡️Revisited Multiple Linear Regression for multi-feature modeling ➡️Learned about Performance Metrics – how to measure predictions ➡️Broke down MSE, MAE, RMSE – when to use what and why

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 8 of #MLOps: Mathematical intuition behind ML models 📦What I explored today: ➡️Go through the Machine Learning techniques ➡️Explored Instance-based vs. Model-based learning ➡️Visualized equations of lines, 3D planes, and hyperplanes Will start Linear regression tomorrow

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 9 of #MLOps: stepping into Linear Regression 📦What I explored today: ➡️Introduction to Simple Linear Regression ➡️Broke down the Linear Regression Equation – slope, intercept, and line fitting ➡️Studied the Convergence Algorithm Let's goooo!

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 9 of #MLOps: stepping into Linear Regression 📦 What I explored today: ➡️Introduction to Simple Linear Regression ➡️Broke down the Linear Regression Equation – slope, intercept, and line fitting ➡️Studied the Convergence Algorithm Let's goooo!

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 8 of #MLOps: Mathematical intuition behind ML models 📦 What I explored today: ➡️Go through the Machine Learning techniques ➡️Explored Instance-based vs. Model-based learning ➡️Visualized equations of lines, 3D planes, and hyperplanes Will start Linear regression tomorrow

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 7 of #MLOps 📦 What I explored: ➡️Performed full EDA on the cleaned Google Play Store dataset ➡️Practiced more data cleaning techniques – handling duplicates, fixing typos, and transforming features ➡️Revised previous topics and practiced some Python questions Let's go!

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 7 of #MLOps 📦What I explored: ➡️Performed full EDA on the cleaned Google Play Store dataset ➡️Practiced more data cleaning techniques – handling duplicates, fixing typos, and transforming features ➡️Revised previous topics and practiced some Python questions Let's go!

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 6 of #MLOps: 📊 Stats + Deep Exploratory Data Analysis! 📦What I explored: ➡️Practiced some Statistics Questions ➡️Performed EDA on the Red Wine Dataset ➡️Cleaned & engineered features for the Flight Price Dataset Will try EDA on the Google Play dataset tomorrow

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 6 of #MLOps: 📊 Stats + Deep Exploratory Data Analysis! 📦 What I explored: ➡️Practiced some Statistics Questions ➡️Performed EDA on the Red Wine Dataset ➡️Cleaned & engineered features for the Flight Price Dataset Will try EDA on the Google Play dataset tomorrow

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Ratan Gulati @ratanstwt

2 months ago

🚀 Day 5 of #MLOps 📦What I explored today: ➡️Started working with Streamlit, built my first interactive ML dashboard! ➡️Began revising Statistics and solved Python-based questions to revise concepts Focusing on Probability & Stats over the next few days and diving into ML