![Animations of Gradient Descent and Loss Landscapes of Neural Networks in Python | by Tobias Roeschl | Towards Data Science Animations of Gradient Descent and Loss Landscapes of Neural Networks in Python | by Tobias Roeschl | Towards Data Science](https://miro.medium.com/v2/resize:fit:679/1*LESP-gCIM4H-WZbX_3LwKw.gif)
Animations of Gradient Descent and Loss Landscapes of Neural Networks in Python | by Tobias Roeschl | Towards Data Science
![Gabriel Peyré on X: "Gradient descent is inefficient to find saddle point (Nash equilibrium) for min-max games, because of spiralling behaviour. Beware when training your GANs … https://t.co/KKKGQ4q9JA https://t.co/xjgLuUHPMU https://t.co/hYYH0xWUXP" / X Gabriel Peyré on X: "Gradient descent is inefficient to find saddle point (Nash equilibrium) for min-max games, because of spiralling behaviour. Beware when training your GANs … https://t.co/KKKGQ4q9JA https://t.co/xjgLuUHPMU https://t.co/hYYH0xWUXP" / X](https://pbs.twimg.com/media/DVqXjvFW0AAc3EU.jpg:large)
Gabriel Peyré on X: "Gradient descent is inefficient to find saddle point (Nash equilibrium) for min-max games, because of spiralling behaviour. Beware when training your GANs … https://t.co/KKKGQ4q9JA https://t.co/xjgLuUHPMU https://t.co/hYYH0xWUXP" / X
![The journey of Gradient Descent — From Local to Global | by Pradyumna Yadav | Analytics Vidhya | Medium The journey of Gradient Descent — From Local to Global | by Pradyumna Yadav | Analytics Vidhya | Medium](https://miro.medium.com/v2/resize:fit:1400/1*ZC9qItK9wI0F6BwSVYMQGg.png)