To perform extensive academic research on a Deep Learning project back in 2018, proved to be the beginning point of my journey in the domain. The work was presented in the conference talks and published. Along with this, completed various projects that made me understand the application part of the field better. So far, I have worked both on structured as well as unstructured data. I'm still enthusiastically grabbing onto other skills and principles that I can integrate into the field.
Components that contribute to my work
• Key packages/ libraries: Pandas, Numpy, Scikit-learn, xgboost, Matplotlib, Seaborn, TensorFlow, Keras, SpaCy, Textblob, Gensim, NLTK, OpenCV
• O.S.: Windows, Linux
• Tools : MS Excel, MS word, Simulink, IBM Watson
• IDE: Jupyter Notebook, Spyder, Google colab, Atom.io
• Code review and documentation: Github
• Interpersonal skills: Leadership, Time management, Communication, Teaching, Team work.