Zeeshan Abbasi

I have extensively self-learned AI and Machine Learning, gaining strong skills in Python, Machine Learning, Deep Learning, NLP, and Data Science through Udemy certifications, Google resources, and YouTube tutorials. My expertise includes working with Scikit-Learn, TensorFlow, PyTorch, and Large Language Models (LLMs) like GPT, LLaMA, Falcon, Mistral, and Bloom. I have built professional AI projects, including an AI Resume Screening Appthat classifies resumes using fine-tuned BERT & GPT models, a Text Summarizer leveraging Transformer-based LLMs, and a Sentiment Analysis model with LSTM and BERT, achieving 92% accuracy. Additionally, I developed Object Detection & Image Classification models using CNNs, ResNet, and EfficientNet and deployed AI models using Flask for real-time applications. My passion for AI has driven me to constantly innovate and apply my skills to real-world problem-solving.

• NLP with Python [Udemy]
• Complete guide to TensorFlow with Python for Deep Learning [Udemy]
• Python for Data Science and Machine Learning [Udemy]
• The Complete Power BI Practical Course 2025 [Udemy]
• Math for Data Science Master Class [Udemy]

• AI Resume Screening App – Fine-tuned BERT & GPT models to classify resumes based on job roles.

• AI Text Summarizer – Built a Transformer-based LLM for generating concise summaries of long texts.

• Sentiment Analysis Model – Developed a LSTM & BERT-based classifier, achieving 92% accuracy.

• Chatbot for Job Assistance – Created an LLM-powered chatbot to assist users in job-related queries.

• News Classification Model – Used Transformer models to categorize news articles into different topics.

• Named Entity Recognition (NER) Model – Built an AI-driven NER system for extracting key entities from text.

• Image Classification Model – Developed a CNN-based classifier using ResNet & EfficientNet.

• Object Detection App – Built an AI model for detecting and labeling objects in images.

• Flask-Based AI Model Deployment – Deployed machine learning models using Flask for real-time inference.