Projects using pandas in Bengaluru
Projects using pandas in Bengaluru
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Aditya Singh
Role: Quantitative Developer Description: Built a custom Python toolkit designed for automated stock return analysis and risk-reward plotting. This project streamlines the portfolio management process by visualizing technical indicators and identifying optimal entry/exit points based on historical data. Tools: Python, Matplotlib, SQL. Impact: Automated the generation of technical reports, replacing 4+ hours of manual spreadsheet work.
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26
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JUNAID ALTAF
LIOTERING DETECTION
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Varun Walekar
I built an AI-powered Data Analyst that turns raw CSV, Excel, or SQL data into executive-ready insights. ✅ Automatic EDA & outlier detection ✅ Visual charts & insights ✅ Executive PDF report ✅ Business recommendations ✅ Voice-based summaries This isn’t a dashboard — it’s an AI analyst for founders and teams who want fast decisions. 🎥 Watch the demo video 📩 Message me “AI Analyst” for access or a custom build #AI #DataAnalytics #Automation #BusinessIntelligence #Streamlit
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Sowmya Lanka
What I built Developed a machine learning solution to predict Buy Box and sales prices using historical analytical data and Linear Regression. How it works Analyzed the data for linear relationships, autocorrelation, multicollinearity, homoscedasticity, and normally distributed errors. Applied Principal Component Analysis (PCA) for dimensionality reduction and to improve model performance. Identified key business factors influencing price prediction. Evaluated the model using R², Adjusted R², RMSE, MAE, and MSE metrics. Technologies Python · Pandas · NumPy · Scikit-learn · Linear Regression · PCA Outcome Built a price prediction model that identified important business drivers and evaluated prediction performance using multiple regression metrics.
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Kavyashree Sanjakadavu
Mental Health Data Analysis Interactive Dashboard
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Abhishek Kumar
Abhishek Kumar’s Post
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6
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Gokulraj G
Geographical_map_visualization
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Sunilgowda S
Prediction of autism spectrum disorder using ML
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Pushkar Gupta
**Supermarket Sales Analysis**
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5
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V A
GitHub - Sirisampada/Image-classification
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Shraddha Ruidas
Kaggle uses cookies from Google to deliver and enhance the qual…
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JUNAID ALTAF
OCR DETECTION
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Sowmya Lanka
What I built Developed a Natural Language Processing (NLP) solution to detect DI Flag issues by analyzing and classifying text descriptions. How it works Cleaned text data by removing hashtags, HTML tags, special characters, and numeric values. Applied text preprocessing techniques including tokenization, stop-word removal, stemming, and lemmatization. Converted text into numerical features using Bag of Words (BoW) and TF-IDF. Trained and evaluated the model using accuracy and confusion matrix metrics. Performed 30 days of validation testing before production deployment. Technologies Python · NLP · Scikit-learn · TF-IDF · Bag of Words · Pandas · NumPy Outcome Built a text classification solution that helped identify DI Flag issues from descriptions and validated the model's performance before deployment.
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Gokulraj G
Data_cleaning
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5
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Pushkar Gupta
Analysiss/supply-chain-analytics-modeling-lightgbm-rnn.ipynb at…
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Gokulraj G
Air_Cargo_Analysis
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