Thanks to visit codestin.com
Credit goes to github.com

Skip to content
View Tahminaaktersonia's full-sized avatar

Block or report Tahminaaktersonia

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse

Popular repositories Loading

  1. Digital-communication_project2023 Digital-communication_project2023 Public

    MATLAB simulation of a digital communication system using M-QAM/PSK modulation, RRC pulse shaping, fading channel, LMS equalizer, and Hamming (7,4) coding. Includes BER analysis, eye diagrams, and …

    MATLAB 1

  2. Radio-Propagation-Project2022 Radio-Propagation-Project2022 Public

    This project simulates radio wave propagation for UMTS 900 MHz, LTE 1800 MHz, and 5G 3500 MHz using MATLAB. It analyzes electric field strength (horizontal and vertical), break point distance, and …

    MATLAB 1

  3. Machin-learning-project-1-sorting-algorithms- Machin-learning-project-1-sorting-algorithms- Public

    A simple Python script that demonstrates sorting using both built-in functions and a custom sorting algorithm.

    Python

  4. Machin-learning-project-3-Nearest-Neighbor-Search- Machin-learning-project-3-Nearest-Neighbor-Search- Public

    Nearest neighbor and analogy search in high-dimensional word embeddings using custom Python implementation.

    Python

  5. Machin-learning-project-2-fit-line- Machin-learning-project-2-fit-line- Public

    Python script for fitting a line y = ax + b to user-clicked points using least squares. Part of DATA.ML.100 – Pattern Recognition and Machine Learning at TAU. Includes manual derivation and plottin…

    Python

  6. Machin-learning-project-4-mnist-bayes-classifiers-dataml100- Machin-learning-project-4-mnist-bayes-classifiers-dataml100- Public

    MNIST and Fashion MNIST classification using 1-NN, Naive Bayes, and Full Bayes classifiers with evaluation and noise handling. Part of Week 4 exercises for TAU's DATA.ML.100 Machine Learning course.