Day92 Deep Learning Lecture Review - Fine-Tuning Models (1)
HW2: Understanding of LoRA and Pre-trained Model Embeddings (ResNet+SBERT) for Visual Question Answering (VQA)
Recent posts
Day91 Deep Learning Lecture Review - Optimizing Hyperparameters
Weights & Biases (W&B) for Monitoring and Fine-Tuning ResNet-18 and Post-Training Evaluations (Dying ReLU, Brightness Robustness)
Day90 Deep Learning Lecture Review - Background Knowledges
HW0: Softmax Properties, PyTorch Lightning, and DataLoader
Day89 ML Review - Ensemble Method (5)
Revisiting Ensemble Method, Random Forest, and XGBoost
Day88 Deep Learning Lecture Review - Lecture 10-12
Deep Learning & Numerical Precision(Floating Point), Hardware Considerations, and Distributed Model Training
Day87 Deep Learning Lecture Review - Lecture 8 (2) & 9
LLMs - Speeding Up LLMs (Grouped Query Attention, KV Caches, MoE, and DPO)
Day86 Deep Learning Lecture Review - Lecture 8 (1)
LLMs- Generating Texts, Positional Encoding, and Fine-Tuning LLMs (LoRA)
Day85 Deep Learning Lecture Review - Lecture 7
LLMs - Perplexity, Tokenizers, Data Cleaning, and Embedding Layer
Day75-84 Introduction to Natural Language Processing using Deep Learning
Basic Machine Learning & Deep Learning, Word Embedding, CNNs, RNNs, LSTM and Transformer
Day74 Deep Learning Lecture Review - Lecture 6
Large Language Model - BERT, GPT, and GPT-2, 3 & 4