This repository contains a collection of my machine learning projects, ranging from supervised learning to natural language processing (NLP). Each project is implemented using Python and various machine learning libraries.
As a fresh graduate with a Bachelor's degree in Software Engineering and a strong understanding of Natural Language Processing (NLP), I have worked on several NLP projects, including text generation, text summarization, classification, and fine-tuning large language models. I have also conducted research for my final year project on Pashto poetry generation using Machine Learning (ML) and Deep Learning (DL), which resulted in two papers: "Pashto Poetry Generation using ML and DL" and "Pashto Poetry Dataset for Deep Learning". Currently, both papers are under review.
Description: Binary classification of breast cancer diagnosis (benign or malignant) using the Breast Cancer Wisconsin (Diagnostic) Dataset. Algorithms: Logistic Regression, Decision Tree, Support Vector Machine (SVM), Random Forest, and K-Nearest Neighbors (KNN). Link to Code Supervised Machine Learning Description: A collection of supervised machine learning projects, including classification and regression tasks. -Notebooks: supervised_machine_learning.ipynb
Unsupervised Learning -Description: A collection of unsupervised machine learning projects, including clustering and dimensionality reduction tasks. -Notebooks: unsupervised.ipynb
-Description: A deep learning project that trains a convolutional neural network to classify handwritten digits from the --MNIST dataset. -Notebooks: mnist_deep_learning.ipynb
-Description: A deep learning project that trains a convolutional neural network to classify images of flowers from the Oxford Flower Dataset. -Notebooks: flower_classification_deep_learning.ipynb
-Description: A deep learning project that trains a recurrent neural network to classify movie reviews as positive or -negative using the IMDB dataset. -Notebooks: imdb_movie_review_classification.ipynb
-Description: A deep learning project that trains a Gated Recurrent Unit (GRU) to generate text character by character using Shakespeare's sonnets as input. -Notebooks: text_generation_using_GRU.ipynb
-Description: A supervised machine learning project that fine-tunes the llama2 language model for text classification using the Dolly Instruct Dataset. -Notebooks: supervised_fine_tune_llama2_with_5kdollyinstruct_dataset_.ipynb
-Description: A deep learning project that trains a Transformer-based model to classify Yelp reviews as positive or negative. -Notebooks: yelp_review_classifier_using_transformer.ipynb
-Description: A deep learning project that generates Pashto poetry using a combination of ML and DL techniques, including LSTM and Transformer-based models. -Notebooks:pashto_poetry_generation_inference.ipynb
-Getting Started with AWS Machine Learning
-Launching into Machine Learning
-Linear Algebra for Machine Learning and Data Science
-Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
pip install -r requirements.txt
You can install the required dependencies using pip:
This project is licensed under the MIT License.
For any inquiries or collaboration opportunities, feel free to reach out to me at [email protected].
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