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zamaex96/README.md
MS

MS

🏆 Reach out to collaborate.🥇

trophy

About Me:

I have research expertise in the domains of Artificial Intelligence, Internet of Things, Underwater Wireless Sensor Network, Underwater Wireless Optical Communication, and RF Communication Component Design. I utilize various tools and simulation techniques to evaluate and develop communication modules, analyze their performance, and publish academic papers that undergo peer review process. I utilize a diverse range of sensor data acquired by undersea and atmospheric sensor nodes to train machine learning models in order to predicts different patterens or parameters.

Social media: 📡

Join me on Linkedin.

LinkedIn

Algorithms Repos

Working on: 🚀

Languages and Tools

Languages:

Python C Embedded C Matlab R Studio
Python C Embedded C Matlab R studio

Best frameworks and main libraries for Python:

Pytorch Selenium Numpy Pandas Sklearn OpenCV
Pytorch Selenium Numpy Pandas sklearn mpl

Platforms

Avr Studio Stm32 IDE Arduino PyCharm Raspberry Pi VS Code
Avr Studio Stm32 IDE Arduino PyCharm Raspberry Pi VS Code

My tools for Data Manipulation & Visualisation:

Conda Plotly Matpltlib
Conda pltly pltly

Tools:

DesignSpark Mechanical Ansys HFSS Multisim MS Office Proteus CISCO Packet Tracer Network Analyzer Antenna Radiation Pattern Analyzer 3D Printing
3d-printer Ansys multisim microsoft-office-2019 circuit cisco-packet-tracer external-oscilloscope-science-and-technology-icongeek26-linear-colour-icongeek26 cellular-network--v1 external-makerbot-industries-an-american-desktop-3d-printer-manufacturer-logo-duo-tal-revivo

OS:

Linux Ubuntu windows Pi OS Mac OS
Linux Ubuntu Windows Pi OS Mac OS

some more supplementary tools.:

TexWorks YAML PyCharm Gitlab Putty Terraterm Agilent Waveforms Photoshop
Latex yaml PC GitLab putty term external-waveform-audio-video-line-ayo-icons-royyan-wijaya adobe-photoshop--v1

snake

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Explore More! 🚀

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  1. ML-LSTM-CNN-RNN-MLP ML-LSTM-CNN-RNN-MLP Public

    Fundamental files to train and evaluate a simple LSTM, MLP, CNN, and RNN model which can be trained on a time-series dataset composed of n input features and m outputs classes.

    Python 2

  2. Explainable-AI-XAI- Explainable-AI-XAI- Public

    This setup provides a basic integration of SHAP into your model training process, enabling you to gain insights into how different features affect the model's predictions. You can further customize…

    Python

  3. Train-MobileNet Train-MobileNet Public

    This code is a script for training an image classification model MobileNet using PyTorch. The code is structured to facilitate easy training, evaluation, and monitoring of a deep learning model for…

    Python

  4. Hybrid-CNN-LSTM-with-Spatial-Attention Hybrid-CNN-LSTM-with-Spatial-Attention Public

    This documents the training and evaluation of a Hybrid CNN-LSTM Attention model for time series classification in a dataset. The model combines convolutional neural networks (CNNs) for feature extr…

    Python 4

  5. SplitImageDataset SplitImageDataset Public

    This Python script is designed to split a dataset of images into training and validation sets. It's particularly useful for preparing data for machine learning tasks, especially in computer vision …

    Python

  6. Aqua-sense Aqua-sense Public

    The algorithm is designed for sensor data processing, employing various combining techniques for robust VLC communication.

    C