Skip to content

Implementation is done in Google Colab. a)Tweets Pre-processing and Cleaning Data Inspection Data Cleaning b)Story Generation and Visualization from Tweets c)Extracting Features from Cleaned Tweets Bag-of-Words TF-IDF Word Embeddings d)Model Building Logistic Regression Support Vector Machine RandomForest XGBoost e)Model Fine-tuning

Notifications You must be signed in to change notification settings

likhitha-pallerla/Twitter_Sentimental_Analysis

Repository files navigation

Twitter_Sentimental_Analysis

Implementation is done in Google Colab.

a)Tweets Pre-processing and Cleaning -Data Inspection
-Data Cleaning b)Story Generation and Visualization from Tweets c)Extracting Features from Cleaned Tweets
-Bag-of-Words
-TF-IDF
-Word Embeddings d)Model Building
-Logistic Regression
-Support Vector Machine
-RandomForest
-XGBoost e)Model Fine-tuning

About

Implementation is done in Google Colab. a)Tweets Pre-processing and Cleaning Data Inspection Data Cleaning b)Story Generation and Visualization from Tweets c)Extracting Features from Cleaned Tweets Bag-of-Words TF-IDF Word Embeddings d)Model Building Logistic Regression Support Vector Machine RandomForest XGBoost e)Model Fine-tuning

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published