Projects
Movies Catalog
Movies Catalog wtih TMDB API. Enable user to create a watchlist
- Developed full-stack movies catalog web (frontend & backend), deployed with docker-compose on GCE VM
- Created user authentication & authorization, search movies, and watchlist features
NestJSNext.jstailwindcssPostgreSQLDockerGCP
Kaggle: Emotion Detection from Text
Emotion detection from text using Tf-idf and Catboost
- Preprocessed the data by transforming dirty data
- Utilized tf-idf and BERT to extract the text features as a vector representation
- Utilized Catboost to develop models and evaluate the its performance
PythonTensorflow
Kaggle: Image Scene Classification
Image scene classification using CNN
- Developed a plain CNN model to classify the image scene
- Replicated the ResNet architecture to extract the image features and use it as the model backbone
- Utilized pre-trained ResNet50 model to improve the model performance
TensorflowPython
EDA: The Ultimate Film Statistics Dataset - for ML
Exploratory Data Analysis on the Ultimate Film Statistics Dataset
- Preprocessed the data by transforming dirty data, splitting column, and reformat the data
- Performed exploratory data analysis to understand the data distribution and correlation between features
- Visualized the data using Matplotlib and Seaborn to gain valuable insights
Python
Kaggle Competition: Spaceship Titanic
Predict the survival of passengers on the Titanic
- Performed exploratory data analysis to understand the data distribution and correlation between features
- Preprocessed the data by transforming dirty data, encoding, and scaling the data
- Utilized Scikit-learn, XGBoost, and Catboost to develop models and evaluate the its performance
Python
Movies Catalog
Movies Catalog wtih TMDB API. Enable user to create a watchlist
- Developed full-stack movies catalog web (frontend & backend), deployed with docker-compose on GCE VM
- Created user authentication & authorization, search movies, and watchlist features
NestJSNext.jstailwindcssPostgreSQLDockerGCP
Kaggle: Emotion Detection from Text
Emotion detection from text using Tf-idf and Catboost
- Preprocessed the data by transforming dirty data
- Utilized tf-idf and BERT to extract the text features as a vector representation
- Utilized Catboost to develop models and evaluate the its performance
PythonTensorflow
Kaggle: Image Scene Classification
Image scene classification using CNN
- Developed a plain CNN model to classify the image scene
- Replicated the ResNet architecture to extract the image features and use it as the model backbone
- Utilized pre-trained ResNet50 model to improve the model performance
TensorflowPython
EDA: The Ultimate Film Statistics Dataset - for ML
Exploratory Data Analysis on the Ultimate Film Statistics Dataset
- Preprocessed the data by transforming dirty data, splitting column, and reformat the data
- Performed exploratory data analysis to understand the data distribution and correlation between features
- Visualized the data using Matplotlib and Seaborn to gain valuable insights
Python
Kaggle Competition: Spaceship Titanic
Predict the survival of passengers on the Titanic
- Performed exploratory data analysis to understand the data distribution and correlation between features
- Preprocessed the data by transforming dirty data, encoding, and scaling the data
- Utilized Scikit-learn, XGBoost, and Catboost to develop models and evaluate the its performance
Python