SELECT * FROM projects WHERE person == ‘DEEJA CHHABRA’;

Forecast Monthly Average Temperature in DFW | TensorFlow, Python, NumPy, Pandas
● Employed ARIMA and FBProphet machine learning model for accurate temperature forecasting.
● Developed informative data visualizations using Power BI to illustrate historical trends and predict temperature.
● Achieved significant accuracy with monthly average temperatures projected at 85.74 (ARIMA), 90.61(FbProphet)

Price Estimation with RFC and XGBoost | TensorFlow, NumPy, Matplotlib
● Implemented Random Forest and XGBoost Regressor for fare estimation, achieving an impressive 0.85 R2 score.
● Transformed categorical features into numerical using label encoding, leading to 25% reduction in training time.
● Leveraged exploratory data analysis (EDA) to uncover insights, leading to a change in feature dimensionality.

Early Detection of 3D printing issues | scikit-learn, pytorch, computer vision, SciPy
● Employed data augmentation on images an visually inspected the results by plotting them to validate.
● Utilized multiple CNN models, tuning them, and leveraging transfer learning with models such as VGG16 to exploit the dataset’s scale and achieve notable performance with a success rate of 99% in anomaly detection.
● Extensive research on ML, DL to apply image segmentation to improve model accuracy by at least 10%.

Text Classification-Pycaret|Naive Bayes|Random Forest|Support Vector Machines|Logistic Regression:
● Sentiment analysis using Pycaret after doing thorough research on Pycaret and it’s text classification.
● Comparison with traditional models (Random Forest, NBC, Logistic Regression, SVM )
● Dataset classified as Positive or Negative based upon the Review Rating.