TensorFlow Tensors(What are Tensors: Understanding the Basics, Creating, and Working with Tensors) Paid Members Public
First off: If you are familiar with NumPy arrays, understanding TensorFlow Tensors will be as easy as first importing TensorFlow as below: import tensorflow as tf print(tf.__version__) # check version # 2.14.0 💡The examples in this article use TensorFlow v2.x, so concepts deprecated and or that were
Implementing Transformer decoder for text generation in Keras and TensorFlow Paid Members Public
The recent wave of generative language models is the culmination of years of research starting with the seminal "Attention is All You Need" paper. The paper introduced the Transformer architecture that would later be used as the backbone for numerous language models. These text generation language models are autoregressive, meaning
Text Classification With BERT and KerasNLP Paid Members Public
BERT is a popular Masked Language Model. Some words are hidden from the model and trained to predict them. The model is bidirectional, meaning it has access to the words to the left and right, making it a good choice for tasks such as text classification. Training BERT can quickly
Top 20 Pandas Functions You Aren't Using, Which You Should Be Using Paid Members Public
This blog post will explore 20 powerful and unique Pandas functions that can significantly enhance your data analysis workflow. We will be using the famous Iris dataset as an example to demonstrate each function. The Iris dataset contains four features: Sepal Length, Sepal Width, Petal Length, and Petal Width, along
How to Build Large Language Model Applications with PaLM API and LangChain Paid Members Public
You can now use Generative AI Studio on Vertex AI to prompt, tune and deploy Google's foundational models, including PaLM 2, Imagen, Codey, and Chirp. You can easily design and fine-tune your prompt and copy the code required to deploy the solution. Leveraging a foundational model is a no-brainer because
How to Perform Image Augmentation With KerasCV Paid Members Public
Training computer vision models with little data can lead to poor model performance. This problem can be solved by generating new data samples from the existing images. For example, you can create new images by flipping and rotating the existing ones. Generating new image samples from existing ones is known
How to Build LLM Applications With LangChain and Openai Paid Members Public
LangChain is an open-source tool for building large language model (LLM) applications. It supports a variety of open-source and closed models, making it easy to create these applications with one tool. Some of the modules in Langchain include: * Models for supported models and integrations * Prompts for making it easy to
How to Train Stable Diffusion With Keras Paid Members Public
Image generation models are causing a sensation worldwide, particularly the powerful Stable Diffusion technique. With Stable Diffusion, you can generate images with your laptop, which was previously impossible. Here's how diffusion models work in plain English: 1. Generating images involves two processes. Diffusion adds noise gradually to the image until
