TensorTonic | Implement Adam Optimizer Step

In this video, I solve the TensorTonic problem “Implement Adam Optimizer Step”, where we implement one update step of the Adam Optimizer from scratch using NumPy.

Adam is one of the most widely used optimization algorithms in deep learning. It combines the idea of momentum and adaptive learning rates to update model parameters efficiently.

In this video, I explain:

✅ What Adam Optimizer is
✅ Why Adam uses first and second moments
✅ Meaning of momentum m_t and velocity v_t
✅ Bias correction in Adam
✅ Step-by-step implementation in Python/NumPy
✅ How the parameter update formula works
✅ Final accepted TensorTonic solution

Видео TensorTonic | Implement Adam Optimizer Step канала AlgorithmsUntilRED