Category Archives: data science

Python Code for AI Exercise: Assigning Sentiment Assignments for unknown words with Large Language Models

#AI Excercise Github Link: Nidhika1121/LLM_Sentiments: LLM_Sentiments (github.com) Now, with this, exercise, sentiment can be assigned to the slangs in languages, even to unknown words, new words occurring in these times of app specific short words, added in our vocabulary. In last article, we saw the AI exercise what 5 class sentiment alignment means. However, theContinue reading “Python Code for AI Exercise: Assigning Sentiment Assignments for unknown words with Large Language Models”

Sentiment Analysis, a Quick Review of Essentials

This is first in series of evaluations of sentiment scores and applying these in useful applications. In coming articles you can see some applications of the topics introduced. Todays topic is of introduction of Sentiment Analysis. This is not a basic’s session but a review session. Sentiment Analysis can be defined in several ways. TheContinue reading “Sentiment Analysis, a Quick Review of Essentials”

Soft Rough Sets for Textual Data Analytics and Language Processing

Here, are some areas we have been working. You shall get glimpses of its workings. For any future work, help, suggestions, you can write to us. This article covers topics on Soft Rough Sets and it’s applications in Text Analytics and Language Processing. The coding shall use Python as much as it can.

Decision Tree using Python With Random Data

Import all required libraries — — — — — — — — — — — — — import pandas as pd from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeClassifier from sklearn import tree import matplotlib.pyplot as plt import random import os — — — — — — — — — — — — — —Continue reading “Decision Tree using Python With Random Data”