Insiya Fatima

Dynamic Python Developer with experience at Ciena, specializing in process automation and data analysis. Proven ability to enhance network efficiency and reliability through innovative solutions. Skilled in machine learning and analytical problem-solving, I excel in collaborative environments, driving impactful results and optimizing performance in complex systems.

Enthusiastic about using data to maximize client acquisition, interaction, and retention. Author of the IEEE paper "Flame Prediction: Using Machine Learning to Tackle Forest Fires," showcasing proficiency in applying cutting-edge analytics to solve practical problems.

- Knowledgeable with Machine and Deep learning models, Python, and SQL, and has practical experience creating data-driven solutions.

Flame Prediction using Machine learning to tackle forest fires - https://ieeexplore.ieee.org/document/10421453 

• Conducted a machine learning-based study for predicting forest fires in the Maharashtra region, using models like Decision Tree, KNN, and Naive Bayes, achieving an accuracy of 96.32% with Decision Tree
• Utilized Python and key libraries such as NumPy, Pandas, and Matplotlib for data manipulation, preprocessing, and visualization of environmental data.
• Applied Scikit-learn for model training and evaluation, optimizing the models based on different features like temperature, humidity, and wind conditions.
• Automated data cleaning and analysis tasks, improving the efficiency and reliability of the results, directly contributing to predictive accuracy.Profciency with data manipulation libraries (e.g., Pandas, NumPy) and big data tools

Deep Learning Approaches for Drowsiness Prediction and Detection - https://ieeexplore.ieee.org/document/10498579

• Developed a deep learning-based system for real-time driver drowsiness prediction by analyzing facial movements.
• Used Python and deep learning libraries such as TensorFlow and Keras for model development, achieving an R-squared value of 93.65% with the Decision Tree model.
• Employed OpenCV for facial analysis and feature extraction, while leveraging Pandas and NumPy
• for data manipulation and preprocessing.
• Integrated PySpark for handling large datasets and optimized model performance for real-time applications, demonstrating the ability to process big data efficiently.

• Merit Certificate, Jamia Millia Islamia
• Pride of School for Academic Performance, Army Public School

• Silver medal for academic performance, Amity University, Noida
• Award for Best Summer Project, Amity University, Noida

• Internship on Discrete Mathematics IIT Delhi