PROGRAMMING LANGUAGES
| Python – Expert | Lua – Expert |
| C Language – Expert | C++ – Intermediate |
| C # – Intermediate | R – Intermediate |
| Matlab – Advanced | PLC – Intermediate |
| JS, HTML, CSS – Expert | Verilog – Advanced |
DEVELOPMENT TOOLS EXPERIENCED
| GitHub | Docker |
| Jenkins | VS-Code |
| Linux-Bash | GNU-Make |
| Toolchains, Cross-compilers |
ML & VISION & NLP FRAMEWORKS HANDS-ON EXPERIENCE
| Pytorch | Scikit-learn |
| XGBoost | OpenCV |
| Pandas | Numpy |
| Transformers – Hugging Face | Gymnasium – RL |
| Open AI GPT Models – using API | OpenAI Chat Assistants |
| Tensorflow | Keras |
ALGORITHMS FAMILIARIZED WITH
| Search Algorithms | |
| Informed (Heuristics) : | A-Star, MiniMax, AlphaBeta |
| Uninformed: | Breadth First (BFS), Depth First (DFS) |
| Uniform-Cost Search | |
| Iterative-Deepening-DFS | |
| Genetic Algorithms | |
| Roulette-wheel Selection | Tournament Selection |
| Fitness Evaluation Functions | Mutation Methods |
| Cross-Over Methods | |
| Reinforcement Algorithms | |
| Bandit algorithms | Dynamic programming |
| Monte-Carlo methods | Q-Learning |
EMBEDDED SYSTEMS ENGINEERING
| FreeRTOS | Digital Control Systems |
| TimeSys Linux | Robotics, Kinematics |
| Digital Filters: FIR, IIR | Comm. Protocols: UART, SPI, I2C |
| MQTT | RS232, RS484-Modbus |
MACHINE LEARNING PROCESS HANDS-ON-EXPERIENCE
| Data Preprocessing | |
| Data Cleaning | Normalization |
| Feature Selection | Dimensionality Reduction |
| Balance Over/Under Sampling | Data Augmentation |
| Training, Validation, & Testing | |
| Data Splitting Methods | Cross-Validation Techniques |
| Regularization Techniques | Hyperparameter Tuning |
| Optimization Algorithms | |
| Model Evaluation & Performance | |
| Classification Metrics | Regression Metrics |
| Ranking Metrics | Model Comparisons |
| Model Optimizations |
Thevananthan Thevarasa 