Data scientist with skills in Python, machine learning, deep learning, and computer vision. Passionate about
applying AI to solve real-world problems through data-driven insights, model development, and deployment.
Exper…
Data scientist with skills in Python, machine learning, deep learning, and computer vision. Passionate about
applying AI to solve real-world problems through data-driven insights, model development, and deployment.
Experienced in CNNs, LSTM, transfer learning, and AI application frameworks such as TensorFlow, Keras, and OpenCV.
Contributed to the research project on RNA secondary structure prediction using LSTM/BiLSTM models.
Focused on data preparation, sequence modeling, and evaluating model performance.
Explored how biological constraints influence predictive accuracy.
Gained hands-on experience in developing and deploying AI models for real-world use cases.
Worked on data preprocessing, model training using LSTM networks, and optimization for predictive analytics and computer vision tasks.
Strengthened deep learning expertise using TensorFlow, Keras, and OpenCV.
Developed a real-time face mask detection system to classify individuals as wearing or not wearing a mask. Implemented a CNN-based model using transfer learning for accurate predictions on live video feed. Applied data preprocessing and augmentation to enhance model performance across diverse lighting and angles. Built a web-based interface using Streamlit/Flask for live demonstration and testing.
Developed a deep learning model using Long Short-Term Memory (LSTM) networks to predict future stock price trends based on historical market data. Integrated Exponential Moving Average (EMA) and Relative Strength Index (RSI) indicators to improve model accuracy.
Designed a deep learning model (LSTM/BILSTM) for predicting secondary structures in RNA sequences. Focused on understanding the impact of helical region constraints on model learning and generalization. Working with synthetically generated datasets and applying rigorous model evaluation techniques.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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