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AI explains AI
- Selection of the Loss Functions for Logistic Regression
- Understanding Stochastic Gradient Descent (SGD)
- Understand the Poission Distribution
- Naive Bayes Theory and Example on Spam Email Detection
- Classification Evaluation: ROC and AUC calcuation
- Reinforcement Learning with the Snake Game
- Simple Decision Trees and Its Implementation
- Understanding K-Means Clustering: A Step-by-Step Guide
- Delve into the Attention Mechanisum
- From Text Transformer to Vision Transformer Model
- GenAI Models Quality Evaluations: Text and Image
- Fine-Tune GenAI Models
- Precomputed Embeddings vs. Real-Time Retrieval (RAG)
GenAI Basics
Interview Tips
Learn with Code
- Selection of the Loss Functions for Logistic Regression
- Understanding Stochastic Gradient Descent (SGD)
- Understand the Poission Distribution
- Naive Bayes Theory and Example on Spam Email Detection
- Classification Evaluation: ROC and AUC calcuation
- Reinforcement Learning with the Snake Game
- Simple Decision Trees and Its Implementation
- Understanding K-Means Clustering: A Step-by-Step Guide
ML Basics
- Selection of the Loss Functions for Logistic Regression
- Understanding Stochastic Gradient Descent (SGD)
- Understand the Poission Distribution
- Naive Bayes Theory and Example on Spam Email Detection
- Classification Evaluation: ROC and AUC calcuation
- Simple Decision Trees and Its Implementation
- Understanding K-Means Clustering: A Step-by-Step Guide