š§ My 160-Day AI Learning Journey Welcome to my 160-day self-taught AI journey, where I go from absolute beginner to job-ready AI Engineer ā one day at a time. This repository contains daily code, projects, and progress, following a carefully crafted roadmap covering:
ā Machine Learning ā¢ ā Deep Learning ā¢ ā NLP ā¢ ā Computer Vision ā¢ ā Generative AI ā¢ ā Deployment ā¢ ā Portfolio Building
š Plan Overview Iām doing professional courses from udemy mastering AI:
š¹ Phase 1: Python & Math Foundations Python Programming Basics Linear Algebra, Probability, Statistics š¹ Phase 2: Machine Learning Supervised & Unsupervised Learning Bagging, Boosting, Stacking, SMOTE Recommender Systems (Content-based, Collaborative, Matrix Factorization) Time Series Forecasting (ARIMA, Prophet, LSTM) š¹ Phase 3: Explainable AI & Model Tuning SHAP, LIME for model interpretability š¹ Phase 4: Deep Learning Neural Networks from scratch TensorFlow, Keras, CNNs, Transfer Learning š¹ Phase 5: Natural Language Processing Text Preprocessing, Word Embeddings, Transformers BERT, Hugging Face, Text Generation, Q&A š¹ Phase 6: Computer Vision OpenCV, CNNs, Image Classification, YOLO, Face Detection, Vision Transformers š¹ Phase 7: Generative AI GANs, VAEs, GPT models, Prompt Engineering LangChain, ChatGPT, Stable Diffusion, RLHF š¹ Final Phase: Deployment & Career Launch Streamlit, Gradio, Hugging Face Spaces, FastAPI AutoML, MLOps basics Resume, LinkedIn, GitHub, Freelance Profiles Capstone Projects, Job Applications, Interview Prep