Saraswata Roy’s Post

Most frequently asked data science interview question : What are the assumptions of Linear regression? Understanding these assumptions is crucial because, regardless of how advanced a model may be, if the data doesn't meet the model's assumptions, the results will not be reliable or accurate. #Linearregression #Stastics #mlmodel #assumptions

#Technology #DataAnalytics #DataDriven 8 Plots for Explaining Linear Regression to a Layman: Explain regression to a non-technical audience with residual, weight, effect and SHAP plots Continue reading on Towards Data Science » #MachineLearning #ArtificialIntelligence #DataScience

Explore various regression models used in predictive analytics. From linear and logistic regression to ridge, lasso, and elastic net, each model serves different data types and relationships. Learn more here - https://bit.ly/4gRvAvv #DataScience #MachineLearning #PredictiveAnalytics #LinearRegression #LogisticRegression #RidgeRegression #LassoRegression #ElasticNet #DASCA

📊 Unlock the power of predictive analytics! From continuous insights to binary solutions, our presentation compares Linear vs. Logistic Regression. 🚀 Explore how these techniques offer nuanced insights and solutions for diverse data-driven challenges. #DataScience #PredictiveAnalytics #MachineLearning

Linear Regression within a single visual representation! Beginning with the basics of Linear Regression, this graphical illustration takes us through the essential steps like Multiple Linear Regression, Gradient Descent, Ordinary Least Squares, and culminating in the advanced technique of Ridge Regression. Each method leads to a deeper understanding, paving the way for comprehensive data analysis. #LinearRegression #DataScience #MachineLearning"

Ever wondered why the normal distribution (bell curve) is everywhere, even when the data seems random? That’s the magic of the Central Limit Theorem (CLT)! The CLT tells us that no matter the original shape of your data (skewed, uniform, or anything else), the average of a large number of samples will always form a normal distribution. Imagine rolling a die—roll it 50 times repeatedly, and those averages start to look like a bell curve! This powerful concept lets us make predictions and decisions, even with non-normal data. #DataScience #Statistics #CentralLimitTheorem #MachineLearning #BigData

"Unlocking insights beyond straight lines! 🔍📈 Fitting a non-linear curve to data can reveal deeper trends and patterns that linear models might miss. Here's a quick demo on how non-linear regression can enhance data interpretation and accuracy. Adding a cube of independent variables improves the fitting of the curve still don't consider it because of its insignificance #DataScience #CurveFitting #NonLinearRegression #DataVisualization #MachineLearning"

🌟 Understanding Lasso vs. Ridge Regression 🌟 As data professionals, we often encounter challenges in building predictive models, especially when dealing with high-dimensional data. Two powerful techniques that can help are Lasso Regression and Ridge Regression. Understanding these differences can help us choose the right approach for our data challenges. Which technique have you found more useful in your projects? Let’s discuss in the comments! 💬 #DataScience #MachineLearning #Statistics #Lasso #Ridge #Regression #FeatureSelection

🔍 Beyond Linear Regression: A Data Science Competition Insight During a recent data science competition, I encountered an intriguing challenge: features showing inverse relationships with heavy right skewness. This scenario made traditional linear regression models inadequate. Key Learnings: Not all data fits the linear model assumption Right-skewed data with inverse relationships needs specialized approaches Enter Tweedie regression with Gamma family - a powerful alternative! Why Tweedie regression? Perfect for positive, continuous data Handles right-skewed distributions naturally No assumption of normal distribution needed 💡 Takeaway: When your data shows non-linear patterns and right skewness, consider Tweedie regression as an effective alternative to traditional linear models. #DataScience #MachineLearning #Regression #Analytics

Unlock the power of data with hypothesis testing! 📊 Dive into the world of t-tests, ANOVA, chi-squared, and linear regression to make informed decisions. Understand p-values and confidence intervals to master your research! #DataScience #HypothesisTesting