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Hey guys,

I wanted my code to be able to differentiate between Pokémon and Digimon, and it did it very well!

fast.ai: pokemon or digimon

Hey everyone, I just finished the first lesson. I found the classifier really interesting, using the knowledge from the jupyter notebooks I created my own classifier that can detect AI in Images with a 90% accuracy.

I think with more data and more training it could be lower but I am happy with the results. I look forward to learning more from the next lessons

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Hi all! Ive made a github pages to show case my work. Created a weasel or pine marten classifier also recreated the pet classifier. Trying to make a Flower classifier at the moment using the Oxford Flower data set.

link to pages: https://shab00.github.io/

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I am a new guy about deep learning, i just finished the Lesson 1, but when i run the code from duckduckgo_search import ddg_images, there is an ImportError: cannot import name ‘ddg_images’ from ‘duckduckgo_search’ (/opt/conda/lib/python3.10/site-packages/duckduckgo_search/init.py) .
I don’t know how to do it. Could anyone can help me?

I have fixed the problem. The ddg_images is not exist. I have changed it to search_images_ddg, and the whole world is quiet.

def search_images(term, max_images=30):
    print(f"Searching for '{term}'")
    return L(search_images_ddg(term, max_images=max_images))
    # return L(ddg_images(term, max_results=max_images)).itemgot('image')

Thank you for your tip, the ddg_images doesn’t exist, should use search_images_ddg method. Thank you.

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I had a similar issue and finally fixed it by modifying the import (duckduckgo_search was not working for me…). Here is the snap of the code in case it’s useful to someone:

from fastbook import search_images_ddg
from fastcore.all import *

def search_images(term, max_images=30):
    print(f"Searching for '{term}'")
    return L(search_images_ddg(term, max_images=max_images))

Hi all, here is a screenshot of my first model. I decided to go for a “string of pearls” vs “string of turtle” plants classifier. I selected the photos myself, ensuring I had a huge variety for both categories, and I adapted the code. It was quite fun :upside_down_face:.

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Hey everyone! I recently finished Lesson 1 and made this fungi image classifier for practice. I was able to get an accuracy of ~93% compared to the original paper’s ~85%. I’d love to hear your thoughts.

Confusion Matrix

Really loving this course (and the fastai library). Looking forward to the rest of it.

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