TensorFlow
Transfer learning guide(With examples for text and images in Keras and PyTorch) Paid Members Public
Training computer vision (CV) or natural language processing (NLP) models can be expensive and requires large datasets. If labeling is done manually, the process will take a longer training time and requires expensive hardware. For instance, the Generative Pre-trained Transformer 2 (GPT-2), a benchmark-setting language model created by Open AI
TensorBoard tutorial (Deep dive with examples and notebook) Paid Members Public
TensorBoard is a visualization library that enables data science practitioners to visualize various aspects of their machine learning modeling. For instance, you can use TensorBoard to: * Visualize the performance of the model. * Tuning model parameters. * Profile the executions of the program. For example, check the utilization of GPUs. * Debug machine
TensorFlow Recurrent Neural Networks (Complete guide with examples and code) Paid Members Public
Recurrent Neural Networks (RNNs) are a class of neural networks that form associations between sequential data points. For example, the average sales made per month over a certain period. The data has a natural progression from month to month, meaning that the sales for the first month are the only
Flax vs. TensorFlow Paid Members Public
Flax is the neural network library for JAX. TensorFlow is a deep learning library with a large ecosystem of tools and resources. Flax and TensorFlow are similar but different in some ways. For instance, both Flax and TensorFlow can run on XLA. Let's look at the differences between Flax and
How to build TensorFlow models with the Keras Functional API (Examples, code, and notebook) Paid Members Public
The Keras Functional API provides a way to build flexible and complex neural networks in TensorFlow. The Functional API is used to design networks that are not linear. In this article, you will discover that the Keras Functional API is used to create networks that: * Are non-linear. * Share layers. * Have
How to create custom training loops in Keras Paid Members Public
Training models in Keras is usually done using the fit method. However, you may want more control over the training process. To do that, you'll need to create a custom training loop. This involves setting up a custom function to compute the loss and gradient. This article will walk you
How to train deep learning models on Apple Silicon GPU Paid Members Public
Training deep learning models on GPUs is faster than training on the CPU, especially when training large image or language models. You can train deep learning models with GPUs on Apple Silicon devices. To train deep learning models with GPU on Apple Silicon devices, you need to install the TensorFlow
How to build CNN in TensorFlow(examples, code, and notebooks) Paid Members Public
In the artificial neural networks with TensorFlow article, we saw how to build deep learning models with TensorFlow and Keras. We covered various concepts that are foundational in training neural networks with TensorFlow. In that article, we used a Pandas DataFrame to build a classification model in Keras. This article
