sanmoyo/nlp_faketweets

3rd year coursework for Machine Learning Technology module at university

NLP_faketweets

3rd year Natural Language Processing coursework for Machine Learning Technology module at university --- my first software project in Python. Unlike my dissertation, this report is fairly short, so feel free to have a look at it in the repo or use the link below.

Link: https://github.com/sanmoyo/NLP_faketweets/blob/main/MLT%20Coursework%20Write%20Up%20(mms2n18).pdf

Components of the project:

1. Training data from MEDIAEVAL 2015 event (not included here as it is from MEDIAEVAL)
2. Test data from MEDIAEVAL 2015 event (not included here as it is from MEDIAEVAL)
3. Jupyter Notebook file of the Machine Learning Technologies Coursework's implementation part by me. (attached in this repo)

Instructions to run the Jupyter Notebook file:

Run with libraries that are used in the implementation code:

i.e. pandas, matplotlib.pyplot, timeit, re, and model specific libraries as shown below:

from sklearn.feature_extraction.text import CountVectorizer

from sklearn.naive_bayes import MultinomialNB

from sklearn.linear_model import SGDClassifier

from sklearn.svm import LinearSVC

from sklearn.feature_extraction.text import TfidfTransformer

from sklearn.feature_extraction.text import TfidfVectorizer

from sklearn.pipeline import Pipeline

from sklearn.metrics import classification_report

from sklearn.model_selection import GridSearchCV