machine learning
10 pieces
Math Foundations of Transformers and MoE Layers
A thorough explanation of the equations powering classic transformer structures and Mixture-of-Experts for advanced deep learning workflows.
Understanding Tokenizers and Embedders in LLM Pipelines
A deep dive into the role, structure, and training of tokenizers and embedders in modern language models like GPT, BERT, and T5.
GPT, PaLM, GLM, LLaMA and beyond: Large language models in medicine
Discover how Large Language Models (LLMs) like GPT, PaLM, GLM, and LLaMA are revolutionizing medicine. Explore applications, challenges, and the future of AI and ML in healthcare.
Power of Multimodal Machine Learning: Challenges, Innovations, and Future Directions
Learn about the transformative impact of multimodal machine learning, highlighting key challenges, recent innovations, and the future of machine learning integration and AI development across diverse data modalities
Understanding Key Insights and Trends in Large Language Models
Learn about how large language models (LLMs) has been made and evolved by looking into its key insights and trends
What is Deep Reinforcement Learning (RL)
Here we introduce language and notation used to discuss RL and explain what RL do
An in-Depth Look at Leading Computer Vision ML Models
Discover top computer vision algorithms and techniques in machine learning, with thorough explanations and ongoing updates.
What is OpenMMLab and how it is used in computer vision
Navigate DevOps, MLOps, and Kaizen in AWS, Azure, and GCP
YOLO and object detection
The YOLO (You Only Look Once) series of fast object detection models has seen significant improvements from YOLOv1 and beyond
Q-learning
Q-learning is a reinforcement learning technique where an agent iteratively learns the value of its actions to navigate towards optimal outcomes in an environment.