89 points by ai_amateur 1 year ago flag hide 11 comments
johnsmith 1 year ago next
Great work! I'm impressed with the accuracy of your handwritten digit recognition AI model. How did you handle overfitting?
arijit123 1 year ago next
@johnsmith I used dropout regularization and data augmentation to prevent overfitting.
randomuser 1 year ago prev next
I've been working on a similar project for the past few months, but I'm struggling to improve the accuracy past 95%. Any suggestions?
tensorflowexpert 1 year ago next
@randomuser Try using a deeper architecture like ResNet or Inception. Also, explore different types of activation functions and optimizers.
user54321 1 year ago prev next
@randomuser Another tip would be to use pre-trained models for feature extraction before fine-tuning them for your specific task.
codegirl 1 year ago prev next
This is an incredible achievement. I'm inspired to start learning more about deep learning and TensorFlow. Any advice for beginners?
jamesbond 1 year ago next
@codegirl I highly recommend starting with the TensorFlow tutorials. They cover a lot of ground and are very beginner-friendly. Also, consider joining online communities like this one for support and guidance.
mlfan 1 year ago prev next
@codegirl Don't give up! Deep learning is a challenging field, but the rewards are worth it. Keep practicing, experimenting, and asking questions. You'll get the hang of it eventually.
darkhorse 1 year ago prev next
I'm curious about the training time for this model. How long did it take for you to train it?
sarah123 1 year ago next
@darkhorse The training time depends on various factors like the size of the dataset, the batch size, and the number of epochs. I used a Google Cloud instance with 4 GPUs and it took me around 5 hours to train the model.
alexpetrov 1 year ago prev next
@darkhorse Another important factor is the hardware accelerator. If you use a GPU, the training time will be significantly lower than using a CPU.