Artificial Intelligence Fundamental Concepts
Natural Neural Network, Artificial Neural Network, and Deep Learning Fundamental Concepts
Image Processing with OpenCV [Colab notebook link]
TensorFlow installation guide
PyTorch installation guide
Google Colab
- TensorFlow 2 quickstart
- TensorFlow Datasets [Catalog]
- Convolutional Neural Network (CNN) [Paper] [Explainer]
- Image classification, [Data Augmentation], [Batch Normalization], [Overfitting], and [Dropout]
- Transfer learning and fine-tuning
- Autoencoders [Paper]
- Variational Autoencoder (VAE) [Paper]
- MusicVAE [Paper] [Reference]
- Generative Adversarial Network (GAN) [Paper1] [Paper2] [Paper3] [Scribble Diffusion] [DALL.E 2] [ChatGPT] [GPTZero]
- Pix2Pix (Image-to-image translation with a [Conditional GAN]) [Paper1] [Paper2] [Reference] [Demo]
- Image Segmentation with U-Net [Paper]
- Recurrent Neural Networks (RNN) [Paper1] [Paper2] [Textbook]
To plot the model:
tf.keras.utils.plot_model(model, rankdir="TD", show_shapes=True)
Parameters:
FC: (the previous layer number of nodes * the next layer number of nodes) + the next layer number of biases
CNNs: (kernel size (w*h) * number of channels * number of filters) + number of biases