Bhabani Sankar Sahoo’s Post

🌟 Unlocking Insights: The Power of Linear Regression Linear regression—a cornerstone of data science and analytics. It’s more than just fitting lines; it’s about understanding relationships, predicting outcomes, and making informed decisions. Whether you’re a beginner or an expert, linear regression invites you to explore data, challenge assumptions, and discover patterns. So, let’s embrace the journey—one equation at a time! p. s. Forgive me for a small typo at page 14 instead of Mean Absolute Error, it's Mean Squared Error. #DataScience #Analytics #LinearRegression #DataDrivenDecisions #AppliedMallu #MachineLearning

Hi folks! Let's make data science a bit more interesting. %% Your Linear Regression Model versus the mighty outlier %% Just like a bouncer at an exclusive club, linear regression models are not fond of outliers. These extreme values can throw off the entire party, leading to skewed results and unreliable predictions. By minimizing the influence of outliers, linear regression ensures our insights are precise and trustworthy. It's all about keeping the data clean and the analysis meaningful! #DataScience #MachineLearning #LinearRegression #Outliers 😁

Master the Art of Predictive Analytics with Regression Techniques  In the dynamic world of data science, Regression Analysis remains a cornerstone for deriving actionable insights and making informed decisions. 📈 From predicting trends to understanding relationships, learn about the most effective techniques like: Linear & Logistic Regression Ridge & Lasso Regression Polynomial Regression ✨ Discover how these methods are transforming industries, optimizing business strategies, and powering innovations. 🔗 https://bit.ly/4fEfDqO #DataScience #RegressionAnalysis #MachineLearning #PredictiveAnalytics #DataInsights

Sequencing different types of #machinelearning methods is so much fun. For example, I worked on a project once that was modeling time-to-event data and used 4 different methods to get to my needed classifier. Here's how it worked: Step 1: Used #RandomSurvivalForests to model right-censored time data and extract the top 5 features by importance Step 2: Built a #clustering algorithm to identify 3 clusters based on the top 5 features from the previous step Step 3: Modeled the right-censored time data with a #KaplanMeier curve to observe the differences by cluster from the previous step Step 4: Used #logisticregression to classify the "high risk" cluster as observed from the survival curve in the previous step using the top five features from the first step There's no one way to solve a problem in #datascience! #data #analytics #predictivemodeling

"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"

Choosing the right data visualization method is crucial for effectively communicating insights. Bar Charts: Use these to indicate values by the length of bars, which can be displayed horizontally or vertically. Histograms: Great for displaying the distribution of a single numerical variable. Line Charts: Perfect for showing trends over time. Scatter Plots: Ideal for showing correlations between values and variables. #DataVisualization #DataScience

Excited to share my first linear regression visualization! 📈 Simple yet powerful, this graph illustrates the relationship between variables. Can't wait to dive deeper into data analysis and visualization! #ML #LinearRegression #DataVisualization

🌟 Excited to dive into the world of Linear Regression! 📉✨ Just wrapped up a comprehensive analysis on predicting global revenue based on production budgets. 🤑💼 Here's a snapshot of the process: 🔍 Data Visualization- Scatter plots to see the correlation between budget and revenue. 🧮 Model Building - Using `scikit-learn`'s LinearRegression to train our model. 📈 Insights - Achieved an R-Squared score of 0.5496, reflecting a moderate fit. This journey was all about exploring real-world data, honing analytical skills, and drawing actionable insights! 🚀 Looking forward to applying these learnings in future projects. #DataScience #MachineLearning #LinearRegression #DataAnalysis #LearningJourney

Hello, Everyone. Sharing insights from my visualization class this semester: - For regression, correlation, and outliers, "scatter plot" is key. - When plotting between terms involving time, opt for a "Line plot." - To visualize percentage share, consider a "Pie-Chart." Efficiency matters in data visualization. These methods make extracting insights easier. 📊 #DataVisualization #Insights #Graphs