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boston-home-price-prediction

boston-house-pricing

churn-prediction

Performed outlier correction using standard box plot method ,then attempted univariate analysis & birative analysis. Checked accuracy using Logic Regression, Decision tree & Random Forest.

covid-analysis

Checked some statistical value like mean, standard deviations & average. Then made visualizations using seaborn, matplotlib, sns.replot & sns.pairplot.

credit-card-fraud-analysis

Handled imbalanced dataset by using sampling method.

demand-forcasting-of-car

Performed EDA then splited the data into train & validation set . Then predicted the demand of the car using sklearn & prophet libraries.

diabetes-statistical-analysis

Used Inferential Statistics, Normal Deviate Z Test & One Sample T-Test in this model.

flight-price-predection

Performed feature selection using heatmap, feature-importance & select k-boost. Then fitted the data using random forest and did hyperparameter tuning.

grip-the-sparks-foundation

mlprojects

movie-recommendation-system

portfolio

I have made a portfolio using Html, Css , Gasp and animations.

spotify-analysis

stock-price-prediction

ted-talk-analysis

I've extracted 6 features for each TED Talk which you can find in this. It includes EDA, Data Analysis, Tabular Data and Python.

the-spark-foundation-data-science-internship

In this I have done following projects : Task1-supervised learning , Task2-unsupervised learning(iris dataset), Task3- EDA.

titanic-survival-predection

Performed EDA , categorial data, splited the data into train & test set using dependent & independent values & built classification model using DECISION TREE CLASSIFIER.