Rapid AI Sentiment Analysis with Python and Scikit Ollama
This tutorial will show you how to quickly set up an AI-powered sentiment analysis using Python and Scikit-Ollama right on your computer. We'll classify financial news headlines, first with a zero-shot classifier that predicts sentiment instantly without any training data, and then move to a few-shot classifier, where we train the model on a handful of labeled examples to refine and enhance its sentiment predictions.
You'll learn how to install and configure Meta's Llama 3 AI model using Ollama. You will also learn how to download and use alternative open source large language models like Google's Gemma 2 and Microsoft's Phi-3.
Scikit-Ollama is a wrapper built on Scikit-LLM (sklearn), which integrates large language models (LLMs) into the scikit-learn framework. This integration allows for seamless incorporation of LLM capabilities into existing machine learning workflows.
Whether you're a data scientist, machine learning engineer, or software developer, this guide will walk you through importing necessary libraries, fetching and preprocessing financial news data, and implementing zero-shot and few-shot classifiers.
If you found this video helpful, give us a like (👍) and subscribe to the Deep Charts channel for more tutorials on the latest AI, machine learning, and data science tools!
Full Code: https://github.com/deepcharts/project...
*Resources*
Ollama: https://ollama.com/
Scikit-Ollama Library: https://andreaskarasenko.github.io/sk...
Scikit-LLM Library (The original package -- uses OpenAI ChatGPT models instead of Ollama): https://skllm.beastbyte.ai/
FinVizFinance Library: https://finvizfinance.readthedocs.io/...
Chapters
0:00 Intro and Ollama Installation
0:35 Python Environment Setup
0:53 Fetching Stock News Headline Data
1:20 Zero Shot Classifier Setup and Prediction
1:57 Few Shot Classifier Training and Prediction
On this page of the site you can watch the video online Rapid AI Sentiment Analysis with Python and Scikit Ollama with a duration of online in good quality, which was uploaded by the user Deep Charts 08 November 2024, share the link with friends and acquaintances, this video has already been watched 4,239 times on youtube and it was liked by 140 viewers. Enjoy your viewing!
