Amanuel M.

As for technology and science jobs, there are opportunities for both lecturers and engineers. My name is Amanuel, but you can call me Aman. Currently, I work as a lecturer in IoT at the Department of Electromechanical/Mechatronics Engineering. I have been working in this field over four years. For my M.Sc. thesis in Mechatronics Engineering, I designed an AI-based autonomous robot intended for hospital use. This robot employs deep reinforcement learning (DRL) and DL-based robots using programming languages such as Python and C/C++. I built a prototype of this robot using the NVIDIA JETSON NANO 2GB developer kit and ARDUINO UNO as master and slave. The SGD (Stochastic Gradient Descent) algorithm is an essential algorithm for Gradient Descent that was used in this project. I also have extensive experience with SolidWorks and AutoCAD and have used MATLAB to implement classical controllers such as PI and PID, interfacing them specifically with SolidWorks. Consequently, I believe I am well-equipped to collaborate with and support individuals in the field of AI and programming. **** SERVICE AREAS **** 🟠 Machine Learning: ✅ Machine learning model development and implementation ✅ Data preprocessing and feature engineering ✅ Supervised learning (classification, regression) ✅ Unsupervised learning (clustering, dimensionality reduction) ✅ Deep learning and neural networks ✅ Natural language processing (NLP) tasks ✅ Recommendation systems ✅ Time series analysis and forecasting ✅ Model evaluation and performance optimization 🔴 Computer Vision: ✅ Image classification and object recognition ✅ Object detection and localization ✅ Image segmentation ✅ Facial recognition and biometrics ✅ Image and video analysis ✅ Feature extraction and representation learning ✅ Optical character recognition (OCR) ✅ Pose estimation and tracking 🟣 Model Evaluation and Performance Optimization: ✅ Model validation and evaluation metrics ✅ Hyperparameter tuning and optimization ✅ Performance optimization for scalability and efficiency ✅ Debugging and troubleshooting ML models **** Proficient in the following PYTHON Libraries for ML/DL projects **** ✔️Tensorflow ✔️ Keras ✔️ PyTorch ✔️ Pandas ✔️ NumPy ✔️ SciPy ✔️ Python Scikit-Learn ✔️ Statsmodels ✔️ Matplotlib ✔️ OpenCV ✔️ PIL **** Successfully Completed jobs in Upwork **** ➡ Emotion detection using CNN on the FER2013 dataset: Video Classification Deep Learning ➡ Stock price prediction using different predictive algorithms: Need an AI expert for stocks ➡ Computer vision using YOLOv5 PyTorch model: Weapon detection using Yolo and SURF Algorithm ➡ Building Predictive model for stocks (ForEex ): Build me a deep learning AI model from my data ➡ Build speech synthesis model using BARK, Tortoise, and SVC pre-trained models: Voice Cloning text to speech (custom voice) ➡ Create an object detection AI model for refrigerators and turn it into an API ➡ Python Developer - Depth-Enhanced CNN Model Specialist ➡ Research and Compare various AI Models ➡ Data Analyst and Engineer **** Successfully Completed projects **** ✳ ML-based Stroke prediction ✳ Apple Price Prediction using RNN/LSTM ✳ Sign Language Recognition System using Random-Forest ML algorithm ✳ Alphabet Recognition (EMNIST) based on OpenCV, Convolutional Neural Network (CNN) ✳ Object Detection-DL and OpenCV ✳ ML-based Stroke prediction: LR, RNN/LSTM, Random-Forest, and Decision-Tree algorithms. ✳ AI/DL-based Autonomous navigating and patient follower robot using Nvidia Jetson Nano DK