I have diverse hands-on experience in data preprocessing, data mining, data optimization, forecasting, database management and machine learning algorithms.
For practical implementation, I have implemented the pipeline for classification of RBD negative and positive patients using raw PSG data, and achieved optimal percentage of accuracy by using different data analysis tools such as Scikit-learn, Scipy, Matplotlib, etc. Also, I worked on the classification of bulk material using the Convolutional Neural Network (CNN) in Python. The CNN model has implemented, validated and tuned. Furthermore, the hyperparameters of model were analyzed using a Tensorboard python package. I have done these projects at research department in Rostock University, Germany.
I have hands-on experience in Python packages including Scikit-learn, Tensorflow, Tensorboard, Numpy, Pandas, Matplotlib, Seaborn, Pygame, Scipy, Pyedf, Pygame, Plotly. Furthermore, I have also designed ETL system using SQL.