Predicting Weather with LSTM and Interactive Visuals

I developed a deep learning-based weather forecasting model using LSTM to predict future conditions from historical weather data. To provide real-time updates, I integrated the OpenWeatherMap API and designed an interactive dashboard using Streamlit and Plotly, enabling dynamic and insightful visualizations. Additionally, I applied data preprocessing, feature engineering, and thorough model evaluation techniques to enhance prediction accuracy and ensure reliable performance.

Tools Used:LSTM (TensorFlow/Keras), Python, Pandas, NumPy, OpenWeatherMap API, Streamlit, Plotly, Matplotlib, Scikit-learn