TensorFlow Tensors(What are Tensors: Understanding the Basics, Creating, and Working with Tensors) 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

Brian Mutea
Brian Mutea

Implementing Transformer decoder for text generation in Keras and TensorFlow 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

Derrick Mwiti
Derrick Mwiti
TensorFlow

Text Classification With BERT and KerasNLP 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

Derrick Mwiti
Derrick Mwiti
TensorFlow

Top 20 Pandas Functions You Aren't Using, Which You Should Be Using 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

Muhammad Anas
Muhammad Anas
Data Science

How to Build Large Language Model Applications with PaLM API and LangChain 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

Derrick Mwiti
Derrick Mwiti
llms

How to Perform Image Augmentation With KerasCV 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

Derrick Mwiti
Derrick Mwiti
TensorFlow

How to Build LLM Applications With LangChain and Openai 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

Derrick Mwiti
Derrick Mwiti
LangChain

How to Train Stable Diffusion With Keras 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

Derrick Mwiti
Derrick Mwiti
TensorFlow