Machine Learning
Sentiment analysis on Twitter uses machine learning and natural language processing (NLP) to analyze tweets and classify them as positive, negative, or neutral. By applying techniques like text preprocessing, tokenization, and feature extraction, machine learning models can detect the sentiment behind tweets.
Every project has a beautiful feature showcase page. It’s easy to include images in a flexible 3-column grid format. Make your photos 1/3, 2/3, or full width.
To give your project a background in the portfolio page, just add the img tag to the front matter like so:
---
layout: page
title: Machine Learning
description: Sentiment analysis on Twitter uses machine learning and natural language processing (NLP) to analyze tweets and classify them as positive, negative, or neutral. By applying techniques like text preprocessing, tokenization, and feature extraction, machine learning models can detect the sentiment behind tweets.
img: /assets/img/Publication_preview/ml_1.jpeg
---




You can also put regular text between your rows of images, even citations (missing reference). Say you wanted to write a bit about your project before you posted the rest of the images. You describe how you toiled, sweated, bled for your project, and then… you reveal its glory in the next row of images.


The code is simple. Just wrap your images with <div class="col-sm">
and place them inside <div class="row">
(read more about the Bootstrap Grid system). To make images responsive, add img-fluid
class to each; for rounded corners and shadows use rounded
and z-depth-1
classes. Here’s the code for the last row of images above:
<div class="row justify-content-sm-center">
<div class="col-sm-8 mt-3 mt-md-0">
{% include figure.liquid path="assets/img/6.jpg" title="example image" class="img-fluid rounded z-depth-1" %}
</div>
<div class="col-sm-4 mt-3 mt-md-0">
{% include figure.liquid path="assets/img/11.jpg" title="example image" class="img-fluid rounded z-depth-1" %}
</div>
</div>