Boston Housing Price Prediction with Multiple Linear Regression

Here is my first Machine Learning model where I used a dummy dataset to predict salary using Linear Regression. The model achieved a prediction accuracy of 95.58% with exploratory data analysis (EDA) implemented in Python and Jupyter Notebook. #Python #JupyterNotebook #Pandas #Matplotlib #MachineLearning

Exploratory Data Analysis (EDA) using Python & Pandas Worked on data cleaning, exploration, and basic visualizations using Pandas and Matplotlib. Sharing a short walkthrough of my analysis workflow. #Python #Pandas #EDA #DataAnalytics #LearningByDoing

📊 Why NumPy Matters in Python NumPy is more than just an array library — it’s the foundation of most data-driven work in Python. From efficient numerical computations to vectorized operations, NumPy enables faster, cleaner, and more reliable data processing. Understanding how NumPy handles memory, broadcasting, and array operations helps write code that is not only correct but also performant. In Data Science and Machine Learning, strong NumPy fundamentals often matter more than complex models. Clean data operations lead to trustworthy results. Building with clarity. Optimizing with purpose. #NumPy #Python #DataScience #MachineLearning #NumericalComputing #CleanCode #DeveloperGrowth

PB Week 5 – Learning Reflection This week, I learned how data visualization using Python helps uncover patterns and insights during exploratory data analysis. By working with Matplotlib and Seaborn, I realized that even simple charts can provide valuable understanding when used with the right purpose. I’ve summarized this learning in a short slide deck. Feel free to check it out. Digital Skola #DigitalSkola #LearningProgressReview #DataAnalytics #Python #DataVisualization

Predicting the future isn’t magic — it’s data science! Learn time series basics, stationarity concepts, and data understanding using Python, Pandas, Matplotlib & Statsmodels. Step-by-step beginner-friendly tutorial by Aionlinecourse Start your forecasting journey now: https://lnkd.in/gdYRDHGM #DataScience #Python #TimeSeries #MachineLearning #Aionlinecourse

🚢 Titanic Dataset – Exploratory Data Analysis I worked on the Titanic dataset to perform exploratory data analysis (EDA). This included data cleaning, handling missing values, and visualizing survival patterns based on gender, passenger class, age, and fare. This hands-on analysis helped strengthen my understanding of how insights are derived from real-world datasets using Python. Tools used: Python, Pandas, Matplotlib, Seaborn #DataAnalysis #Kaggle #Python #EDA #Learning

🎥 Project Demo | Student Performance Prediction Here’s a short walkthrough of my Python project where I analyzed student performance data. 🔹 Loaded and analyzed the dataset using Pandas   🔹 Created a new feature (final score)   🔹 Visualized data using Matplotlib & Seaborn   🔹 Used histograms and correlation heatmaps for insights  This project helped me understand Exploratory Data Analysis (EDA) and data visualization concepts in a practical way. 📌 Tools: Python, Pandas, Matplotlib, Seaborn, Jupyter Notebook  Open to feedback and learning opportunities 🚀 #Python #DataAnalysis #EDA #MachineLearning #StudentProject #LearningByDoing

Day 06 of my NumPy Revision ✅ Today I revised how to handle missing (NaN) and infinite values using NumPy. These concepts are very important for data preprocessing and machine learning. ✔ np.isnan() – detect missing values ✔ np.nan_to_num() – replace NaN and infinite values ✔ np.isinf() – detect infinite values ✔ np.isfinite() – validate clean numeric data I am documenting my complete learning journey step-by-step on GitHub. More revisions coming soon on Pandas #NumPy #DataScience #Python #MachineLearning #LearningJourney #GitHubPortfolio

Excel, Python, and R may look different but under the hood, they have some similarities Here’s a simple side-by-side comparison of common Excel functions and their equivalents in Python and R, covering: Descriptive statistics Logical conditions Lookups Math, text, and date functions Different tools with same statistical logic Great for students, analysts, and anyone transitioning from Excel to programming-based data analysis. #DataAnalytics #Excel #Python #RStats #Statistics #DataScience #LearningJourney

🚀 House Price Prediction | Machine Learning Project Built a machine learning regression model to predict house prices using Python. Performed data cleaning, EDA, feature encoding, model training, and evaluation. Tech Stack: Python | Pandas | NumPy | Scikit-learn | Matplotlib | Jupyter Notebook GitHub Project: https://lnkd.in/ggrBHjNM #MachineLearning #DataScience #Python #MLProject #LearningJourney