Junaid Khan

Hello! I'm a passionate and highly motivated Machine Learning Engineer in the early stages of my professional journey. With a solid foundation in Python programming, I specialize in developing ML solutions that are clean, efficient, and tailored to client needs. My core strengths lie in data preprocessing, exploratory data analysis (EDA), and building models for classification, regression, and clustering tasks using scikit-learn, Pandas, and NumPy.

Although I consider myself a beginner, I’m actively expanding my skillset into more complex domains such as deep learning, natural language processing (NLP), and computer vision. I’m currently working with tools like TensorFlow, Keras, and PyTorch to build neural networks for image classification, sentiment analysis, and more. I also have hands-on experience with data visualization libraries such as Matplotlib, Seaborn, and Plotly, which help communicate insights clearly and effectively.

In addition to technical skills, I understand the importance of model evaluation and performance metrics like accuracy, precision, recall, F1-score, and ROC-AUC. I also implement techniques like cross-validation, feature scaling, and hyperparameter tuning to improve model performance.

I’m comfortable working with Jupyter Notebooks, Google Colab, and Git/GitHub for version control. I'm also exploring MLOps fundamentals, including model deployment using Flask and Streamlit, and using platforms like Hugging Face and Kaggle to sharpen my skills with real-world datasets.

My goal is to collaborate with clients who value clarity, transparency, and growth. Whether you need a small predictive model, a custom data pipeline, or someone to clean and prepare your data — I'm here to help. I treat every project as a learning opportunity and always strive to deliver work that adds value.