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evitanegaraputri4/README.md

👋 Hi, I'm Evita Negara Putri

🎓 About Me

I am currently pursuing a Master's degree in Data Science and Applied Analytics at the University of Lincoln in the United Kingdom. I hold a Bachelor's degree in Information Technology from Udayana University in Indonesia.

📈 Professional Experience

With a solid foundation in data science and applied analytics, I am eager to continue advancing my knowledge and skills in machine learning, data analytics, and AI to drive business impact. With more than three years of experience in digital marketing analytics, I have adeptly combined my industry knowledge with technical expertise in data science. This unique blend allows me to extract valuable insights from data, driving informed decision-making and supporting business growth. I am enthusiastic about embracing new challenges and collaborating on innovative data science projects while leveraging my skills and knowledge to contribute effectively to a dynamic team in the field.

🛠️ Technical Skills

  • Programming Languages: Python, MYSQL, R
  • Data Science Skills: Machine Learning, Deep Learning, Big Data Analytics
  • Tools & Technologies: Pandas,TensorFlow, Keras

📫 How to Reach Me

Feel free to check out my Data Science projects in the repositories below:

Popular repositories Loading

  1. Vehicle-Classification Vehicle-Classification Public

    Efficient vehicle classification using machine learning and deep learning models for Intelligent Traffic Systems. Classifies five vehicle types with models like SVM, Random Forest, and CNN, utilizi…

    Jupyter Notebook

  2. House-Price-Prediction-Using-Spark-ML House-Price-Prediction-Using-Spark-ML Public

    House price prediction for Pakistan’s real estate market using PySpark. This project applies linear regression to analyze factors like location, size, and amenities, supporting informed decision-ma…

    Jupyter Notebook

  3. Weed-Classification Weed-Classification Public

    Weed classification using image processing and machine learning to boost agricultural productivity. This project classifies Charlock and Cleves weeds with models like logistic regression, SVC, rand…

  4. Text-Processing-Classify-Topic-Label Text-Processing-Classify-Topic-Label Public

    This project classifies BBC News articles into five topics—Sport, Business, Politics, Tech, and Entertainment—using Naïve Bayes, Random Forest, and SVM. Feature extraction with TF-IDF and Bag of Wo…

    Jupyter Notebook

  5. Weather-Prediction-Using-Timeseries-Data Weather-Prediction-Using-Timeseries-Data Public

    This project enhances agricultural weather forecasting by predicting solar radiation (SRAD) using machine learning and deep learning models, including KNN, Random Forest, XGBoost, LSTM, and hybrid …

    Jupyter Notebook

  6. evitanegaraputri4 evitanegaraputri4 Public