NumPy - for array manipulation and algebraic operations (matrix multiplication) Pandas - for dataframes Scikit-Learn - for general machine learning XGBoost - gradient boosting trees implementation Flask - for serving the models TensorFlow or PyTorch or MXNet - for deep learning Matplotlib and Seaborn - for visualization Airflow - for building data pipelines