Ayushi Jain's repositories
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.
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.
Flight-Price-Predection
Performed feature selection using heatmap, feature-importance & select k-boost. Then fitted the data using random forest and did hyperparameter tuning.
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.
Diabetes-Statistical-Analysis
Used Inferential Statistics, Normal Deviate Z Test & One Sample T-Test in this model.
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.
Credit-card-fraud-analysis
Handled imbalanced dataset by using sampling method.