- Building Machine Learning & Data Science projects from scratch
- Learning Deep Learning, Neural Networks & AI systems
- Improving problem solving with Python and real datasets
- Growing my portfolio for internships & opportunities
- Plants Diesease Classification (CNN): Built using Resnet18 Transfer Learning
- Data Preprocessing & Outlier Detection: Real-world preprocessing techniques and outlier handling.
- ML Mini Projects: Small projects to practice core machine learning concepts.
- Cross Validation Model: Data analysis and visual storytelling using Python libraries.
- Upcoming Deep Learning Projects: CNNs, RNNs, and advanced AI models coming soon.
kartik@github
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OS : Windows x64
Shell : PowerShell
Terminal : VS Code
Dev Env : Python + Jupyter
Languages : Python, SQL
Libraries : NumPy, Pandas, Matplotlib, Seaborn
ML Stack : Python, NumPy, Pandas, Scikit-learn, PyTorch
Interests : Machine Learning, Deep Learning, Gen AI
Goal : AI Engineer 🚀


