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This repo consists of notebooks I created to work upon the skills I learnt through several courses. All notebook has EDA, Model Building, Hyperparameter Tuning, Ensemble Models and Sampling Techniques.

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ritik872000/Data-Science-Portfolio

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Black Friday Sales Prediction

Black Friday Sales Prediction

 
 

Crop Yield Classification

Crop Yield Classification

 
 

HR Analytics

HR Analytics

 
 

Loan Prediction

Loan Prediction

 
 

NLP Text Cleaning

NLP Text Cleaning

 
 

Seaborn

Seaborn

 
 

Sentiment Analysis

Sentiment Analysis

 
 

Titanic Survival Prediction

Titanic Survival Prediction

 
 

readme.md

readme.md

 
 

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Data-Science-Portfolio

  1. Black Friday Sales Prediction: This notebook includes Data Cleaning(Taking care of missing values, Scaling, encoding), Data visualizations(univariate and bivariate analysis) and model building.

  2. Crop Yield Classification: This notebook includes Data Cleaning(Taking care of missing values, Scaling, encoding), Data visualizations(univariate and bivariate analysis) and model building.

  3. HR Analytics: This notebook includes Data Cleaning(Taking care of missing values, Scaling, encoding), Data visualizations(univariate and bivariate analysis), model building, Hyperparameter Tuning(Grid Search).

  4. Loan Prediction:This notebook includes Data Cleaning(Taking care of missing values, Scaling, encoding), model building and result comparison.

  5. NLP Text Cleaning: This notebook has basic steps of text cleaning(removing @, #, urls, etc) , stemming and tokenization.

  6. Seaborn: This notebook has various seaborn plots (Countplot, Swarmplot, scatterplot, relplot, catplot, violinplot, catplot, HEX plot, KDE plot and Heatmap)

  7. Sentiment Analysis: This notebook has basic steps of text cleaning(removing @, #, urls, etc) , stemming, tokenization, Vectorizer, Oversampling and model building.

  8. Titanic Survival Prediction: This notebook includes Data Cleaning(Taking care of missing values, Scaling, encoding), Data visualizations(univariate and bivariate analysis) and model building.

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This repo consists of notebooks I created to work upon the skills I learnt through several courses. All notebook has EDA, Model Building, Hyperparameter Tuning, Ensemble Models and Sampling Techniques.

Topics

nlp machine-learning eda seaborn hyperparameter-tuning bivariate-analysis ensembling data-visualizations

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