Master Python, Machine Learning, Deep Learning, Generative AI, Transformers, and LLMs through hands-on coding and real-world projects. Build practical AI skills from foundational concepts to real-world applications.
Introduction to Advanced AI & Machine Learning • 1 lessons
Ensemble Learning – Bagging, Boosting, Random Forest & AdaBoost • 1 lessons
XGBoost – Gradient Boosting, Implementation & Evaluation • 1 lessons
Hyperparameter Tuning – Grid Search, Random Search & GridSearchCV • 1 lessons
Artificial Neural Networks – Architecture, Activation Functions & Forward Propagation • 1 lessons
Deep Learning Model Training – Adam Optimizer, Dropout & Training Pipeline • 1 lessons
Convolution, Pooling, Feature Maps & Image Classification • 1 lessons
Transfer Learning – VGG16, Feature Extraction & Fine-Tuning • 1 lessons
RNN & LSTM – Sequential Data, Memory Gates and Time-Series Forecasting • 1 lessons
Advanced NLP – Transformers, LLMs, BERT & Prompt Engineering • 1 lessons
Transformers & BERT – Self-Attention, Q/K/V and Fine-Tuning • 1 lessons
RAG – Embeddings, Vector Databases, Semantic Search & LLM Integration • 1 lessons
Explainable AI – SHAP, Feature Importance & CNN Visualization • 1 lessons
AI Model Deployment Using Flask – Build an AI Prediction Web Application • 1 lessons
RoBERTa-Based Text Classification with Flask – End-to-End AI Project • 1 lessons
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