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What are some limitations of a deep learning model?

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What are some limitations of a deep learning model?

Drawbacks or disadvantages of Deep Learning ➨It requires very large amount of data in order to perform better than other techniques. ➨It is extremely expensive to train due to complex data models. Moreover deep learning requires expensive GPUs and hundreds of machines. This increases cost to the users.

How do you retrain inception model?

Train Inception with Custom Images on CPU

  1. Download the tensorflow-for-poets-2. Let’s start by making a new folder Flowers_Tensorflow.
  2. Download the dataset. Go to this link and download the flower data.
  3. Retrain the model.
  4. Test the newly Trained Model.

What are the limitations of transfer learning?

What are the disadvantages of transfer learning? – Quora. Currently, one of the biggest limitations to transfer learning is the problem of negative transfer. Transfer learning only works if the initial and target problems are similar enough for the first round of training to be relevant.

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What is the difference between inception V2 and inception v3?

In the Inception V2 architecture. The 5×5 convolution is replaced by the two 3×3 convolutions. As we discussed above that a 3×3 convolution can be converted into 1×3 then followed by 3×1 convolution which is 33\% cheaper in terms of computational complexity as compared to 3×3.

What may be the limitation of deep learning and why?

Deep Learning lacks common sense. This makes the systems fragile and when errors are made, the errors can be very large. These are part of concerns and thus, there is a growing feeling in the field that deep learning’s shortcomings require some fundamentally new ideas.

How do I retrain a TensorFlow model?

Steps in Retraining Object Detection Models with TensorFlow:

  1. Setting up TensorFlow & the API.
  2. Creating the image dataset.
  3. Labelling images.
  4. Training the TensorFlow model.
  5. Retraining the model with your data.
  6. Exporting your object detection model.

How do you train an image classifier using TensorFlow?

Image classification

  1. On this page.
  2. Import TensorFlow and other libraries.
  3. Download and explore the dataset.
  4. Create a dataset.
  5. Visualize the data.
  6. Configure the dataset for performance.
  7. Standardize the data.
  8. Compile the model.
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What are the disadvantages of transfer?

Disadvantages of Transfer function

  • Transfer function does not take into account the initial conditions.
  • The transfer function can be defined for linear systems only.
  • No inferences can be drawn about the physical structure of the system.

Why is inception v3 better than other models?

The Inception V3 model used several techniques for optimizing the network for better model adaptation. It has a deeper network compared to the Inception V1 and V2 models, but its speed isn’t compromised. It is computationally less expensive. It uses auxiliary Classifiers as regularizes.

What is Inception V2 model?

Inception-ResNet-v2 is a convolutional neural network that is trained on more than a million images from the ImageNet database [1]. The network is 164 layers deep and can classify images into 1000 object categories, such as keyboard, mouse, pencil, and many animals.