Gradients are essentially vectors of partial derivatives of the neural network's loss function concerning its weights and biases. The loss function quantifies the difference between the predicted output of the neural network and the actual target values

One of the best websites to learn prompting on your own

This repo gives you all the prompts you need when working with Nano Banana Pro

{
"image_denoscription": {
"subject": {
"face": {
"preserve_original": true,
"reference_match": true,
"denoscription": "The girl's facial features, expression, and identity must remain exactly the same as the reference image."
},
"girl": {
"age": "young",
"hair": "long, wavy brown hair",
"expression": "puckering her lips toward the camera",
"clothing": "black hooded sweatshirt"
},
"puppy": {
"type": "small white puppy",
"eyes": "light blue",
"expression": "calm, looking forward"
}
},
"environment": {
"setting": "outdoors in a winter scene",
"elements": [
"snow covering the ground",
"bare trees in the background",
"blurred silver car behind the girl"
],
"sky": "clear light blue sky"
},
"mood": "cute, natural, winter outdoor moment",
"camera_style": "soft depth of field, natural daylight, subtle winter tones"
}
}