Machine Learning Engineer | Deep Learning Enthusiast | AI-Powered Solutions Developer
- 🎓 Software Engineering graduate from UET Taxila
- 💼 Currently seeking opportunities in Software Engineering / Machine Learning
- 🧠 Interests: Machine Learning • Deep Learning • NLP • Computer Vision
- 🚀 Building: Real-world AI applications, model deployment systems & cool dashboards
- 🛠️ Tools I Use Daily: Python, TensorFlow, PyTorch, FastAPI, Docker, Wandb
- 📫 Reach me anytime: yousaf.mlengineer@gmail.com
- 🌐 Portfolio: yousafrana.me
- 📘 Machine Learning Specialization – Offered by Stanford University and deeplearning.ai, taught by Andrew Ng. Covers foundational ML algorithms, model evaluation, and deployment practices.
- 🧠 Deep Learning Specialization – A 5-course series by deeplearning.ai, focused on Neural Networks, CNNs, RNNs, and NLP, also led by Andrew Ng.
- 🔧 MLOps Specialization – From Duke University. Focuses on the full ML lifecycle: data versioning, model deployment, CI/CD, and monitoring in production.
- 📌 20+ ML/DL and Full-Stack Projects
- 🤖 Creator of Summedify – a multi-modal media summarization platform
- 🧪 Researcher: PubMed RCT Summarization using Biomedical Embeddings
- 🧠 Trained & Deployed models like Whisper, ResNet, TinyLLaMA, Phi-2, Food101, etc.
- 🧩 Expertise in LoRA, ONNX, Hugging Face, .nemo, .gguf formats
- 🌍 Member of a professional AI team (ML Engineers, Python & App Devs)
- 💼 Open to collaborations, freelance, and AI startup opportunities
🎥 A multi-modal summarizer built using Whisper V3, Transformers & Streamlit.
🔗 Converts speech or documents to summarized text in seconds.
🛠️ Tech Stack:
🔧 Deployed GPT-2 on Azure with full MLOps pipeline using Docker & CI/CD.
☁️ Hugging Face Transformers + Azure Container Registry = production-grade NLP.
🛠️ Tech Stack:
An advanced transcription system that converts audio and video speech into accurate text using OpenAI’s Whisper Large V3 model via Hugging Face.
🧠 Supports multiple media formats and uses audio splitting for high accuracy.
🛠️ Tech Stack:
🧠 Classifies biomedical sentences into Objective, Methods, Results, etc.
📚 Helps researchers skim abstracts faster using NLP & Hugging Face.
🛠️ Tech Stack:
⚖️ Debiased fake news dataset using TF-IDF + Naive Bayes + CNN layers.
🛠️ Tech Stack:
🧪 Used DREAMERDataset to classify EEG signals. Exported to ONNX for real-time use.
🛠️ Tech Stack:
🧰 Built a command-line tool using Python Fire to extract and summarize Wikipedia entries.
🛠️ Tech Stack:
“Code with purpose. Deploy with confidence. Learn endlessly.”