I'm passionate about Machine Learning, Data Science, Large Language Models (LLMs) and Generative AI.

I love exploring how AI can solve real-world problems and create new possibilities. Always excited to learn and share cool projects!

I have 2+ years of experience building and deploying machine learning and deep learning models.

I have a strong practical and theoretical experience in the development of Machine Learning Models and Computer Vision.

🔭 Some of the notable courses I have completed and that helped in gaining strong theoretical foundation include:

• Machine Learning Certification by Stanford University
• Deep Learning Specialization by Andrew Ng
• Data Science Professional Certificate by IBM
• Python for Everybody Specialization by University of Michigan

🔭 I've used different Machine Learning and Deep Learning models in real-time projects. Below are some used models:

• Linear Regression
• Logistic Regression
• Support Vector Machines (SVM)
• Decision Trees (DT)
• Random Forests (RF)
• K-Nearest Neighbors (KNN)
• Deep Neural Networks
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN)
• Naive Bayes (NB)
• Gradient Boosted Decision Trees (GBDT)
• XGBoost
• Long Short-Term Memory (LSTM)

🔭 Below are some state-of-the-art (SOTA) time series forecasting models used in various real-time projects:

• Auto-Regressive (AR) Model
• Auto-Regressive Moving Averages (ARMA) Model
• Auto-Regressive Integrated Moving Averages (ARIMA) Model
• Neural Hierarchical Interpolation of Time Series (N-HiTS) Model
• Seasonal Auto-Regressive Integrated Moving Averages (SARIMA) Model
• The Prophet Forecasting Model by Facebook

🔭 Furthermore, below are some of the tools used during my experience for Generative AI:

• Langchain
• LangGraph
• Retrieval Augmented Generation (RAG)
• Llama Index
• OpenAI API
• Mixtral (LLM)
• Llama 2 (LLM)
• GPT - 3 (LLM)
• GPT - 3.5 (LLM)
• GPT - 4 (LLM)

These valuable tools and techniques have empowered me to successfully develop and comprehend intricate machine learning projects.

The following links include detailed descriptions within each GitHub repository:

🚀 Heart Disease Prediction using Machine-Learning	👨🏻‍💻 Loan Default Risk Analysis

🏭 Food Vision Classification	☎️ Customer Analytics

🚀 Dog Breed Classification	👨🏻‍💻 Bulldozer Sales Prediction