BIG Mistake in Adam | Adam vs AdamW скачать в хорошем качестве

BIG Mistake in Adam | Adam vs AdamW

In this video we clearly explain the difference between Adam optimizer and AdamW optimizer used in deep learning and machine learning. Many people use Adam without understanding how weight decay and L2 regularization behave inside adaptive optimizers. This video explains: • Why momentum uses mean of gradients • Why RMSProp uses squared gradients • What weight decay actually means • How L2 regularization changes the gradient • Why Adam mixes weight decay incorrectly • How AdamW fixes the problem with decoupled weight decay This topic is important for anyone working in: Deep Learning Machine Learning Neural Networks Transformers PyTorch / TensorFlow models Most modern models like BERT, GPT, and Vision Transformers use AdamW, so understanding this optimizer is essential. If you are preparing for ML interviews, research, or building deep learning models, this explanation will help you understand optimizers more clearly. #AI #MachineLearning #Transformers #LLMs #DeepLearning #ArtificialIntelligence #GPT #BERT #OpenAI #BuildAIwithSandeep #optimizers #adamw