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Coursera Project Network

Text Generation with Cohere: Recognizing Similarities

Coursera Project Network via Coursera

Overview

In this 1-hour long project-based course, you will learn how to install Python packages working with Cohere's API, integrate external APIs like Cohere in a Python script, use embeddings to analyze semantic similarity between text and generate text with Cohere's language models. In today's world, where artificial intelligence and natural language processing are revolutionizing the way we interact with data, understanding how to harness these technologies is more important than ever. This project-based course is designed to immerse you in the world of AI-driven text analysis and generation using Cohere, a cutting-edge language model. Throughout this course, aimed at data enthusiasts and budding AI practitioners, you will learn how to integrate external APIs into a Python script, analyze semantic similarity between texts using embeddings, and generate contextually relevant text with Cohere's language models. By navigating through a series of hands-on tasks, you will create a versatile Python application capable of insightful text analysis and creative text generation. This project stands out because it offers a practical, real-world application of advanced AI techniques in a user-friendly manner. To make the most out of this course, a basic understanding of Python programming is recommended.

Syllabus

  • Project Overview
    • In this project you will build basic Python scripts to explore Cohere's API endpoints, covering text-embeddings for semantic similarity analysis, and text generation with Cohere's Large Language Models (LLMs).

Taught by

Parth Patil

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