@datascibykashi: Today I explored how Linear Regression helps us find relationships between variables — by fitting the best possible straight line through data points. 💡 It’s one of the simplest yet most powerful algorithms in Machine Learning! It predicts outcomes using the equation: 👉 Y = mX + b where m is the slope and b is the intercept. 🔍 Key Concepts I learned: • Finding the line of best fit using least squares. • Understanding residuals (errors) between predicted and actual values. • Evaluating model performance using R² score & Mean Squared Error (MSE). • Visualizing regression lines to see how models learn trends. 🧠 Tech Used: Python | NumPy | Pandas | Matplotlib | Scikit-learn Linear Regression might look simple, but it’s the backbone of predictive analytics — from stock prices to sales forecasts! 💪 #MachineLearning #LinearRegression #DataScience #AI #Python #100DaysOfML #DeepLearning #PredictiveAnalytics #MLForBeginners #CodingJourney #TechEducation

Data Scientist | Kashi

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Saturday 25 October 2025 07:40:26 GMT