About Me
I am a PhD graduate with a background in Electronic and Computer Systems Engineering.
I have several years of experience working with data, mainly data analysis, statistical modelling and
applying machine learning techniques and algorithms to solve problems throughout the research I conducted
during my candidature, as well as through an Internship I undertook.
I also have self-studied several areas related to machine learning, including NLP and Computer Vision, and
have a comprehensive knowledge and practical experience in this area.
In addition, prior to starting my PhD, I have worked as a Senior Corporate Applications Engineer at a
leading software company for almost 3 years, where I have acquired many transferable skills and experience
related to software development, verification, project management while working as a team player.
Technical Skills :
- Data Wrangling, Exploratory Data Analysis & Feature Engineering
- Database and Query (SQL)
- Statistics and Hypothesis Testing
- Regression (Linear, Logistic)
- Classification - (K-NN, Naive Bayes, SVM, Decision Trees, Random Forest, Boosting)
- Clustering - (K-Means, HA Clustering, DBScan, MeanShift) and Dimentionality Reduction (PCA)
- Deep Learning (Multilayer Perceptron, CNN, RNN, GAN)
- Time Serise Analysis
Tools:
| Python | SQL | Pandas | Numpy | SciPy |
| Java | C++ | JavaScript | HTML | CSS |
| Scikit-Learn | XGBoost | TensorFlow | Keras | |
| Linux | Scripting | GIT | ||
| Apache Spark | PySpark | Scala | Azure | |
| Tableu | PowerBI | |||
| MATLAB | Mathematica | COMSOL | ||
| Verilog | System Verilog | VHDL |