Fake News Detection with Machine Learning

Project Description

In this project, a Machine Learning model will be developed to detect fake news using the Fake and Real News Dataset from Kaggle (https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset). This dataset contains news articles labeled as real or fake, allowing us to train and evaluate classification algorithms.

Objective

The main objective is to build a model capable of distinguishing between real and fake news with high accuracy. This will help analyze patterns in the language used in each category and explore Natural Language Processing (NLP) approaches.

Methodology

• Data Exploration and Cleaning: Analyzing dataset characteristics, removing irrelevant data, and preprocessing the text.

• Text Analysis: Tokenization, stopword removal, lemmatization, and vectorization (TF-IDF, Word Embeddings, etc.).

• Model Training: Comparing different classification algorithms (Logistic Regression, Random Forest, SVM, Neural Networks).

• Evaluation and Optimization: Using metrics such as accuracy, recall, and F1-score to measure model performance.

• Deployment and Interpretation: Implementing the model and analyzing the most relevant features for classification.

Expected Results

• Identify the most relevant text features for detecting fake news.
• Develop a model with high accuracy in classifying real and fake news.
• Explore the impact of different preprocessing techniques and machine learning models.

Set up your Environment

Please make sure you have forked the repo and set up a new virtual environment.

The added requirements file contains all libraries and dependencies we need to execute the NLP notebooks.

Note:

• If there are errors during environment setup, try removing the versions from the failing packages in the requirements file. silicon shizzle.

• In some cases it is necessary to install the Rust compiler for the transformers library.

• make sure to install hdf5 if you haven't done it before.

• Check the rustup version by run the following commands:

  rustup --version

  If you haven't installed it yet, begin at step_1. Otherwise, proceed to step_2.

macOS type the following commands :

• Step_1: Update Homebrew and install rustup and hdf5 by following commands:

  brew install rustup
  rustup-init

  Then press 1 for the standard installation.

  Then we can go on to install hdf5:

   brew install hdf5

  Restart Your Terminal and then check the rustup version by running the following commands:

  rustup --version

• Step_2: Install the virtual environment and the required packages by following commands:

  NOTE: for macOS with silicon chips (other than intel)

  pyenv local 3.11.3
  python -m venv .venv
  source .venv/bin/activate
  pip install --upgrade pip
  pip install -r requirements_silicon.txt

  NOTE: for macOS with intel chips

    pyenv local 3.11.3
    python -m venv .venv
    source .venv/bin/activate
    pip install --upgrade pip
    pip install -r requirements.txt

WindowsOS type the following commands :

• Step_1: Install rustup by following :

  1. Visit the official Rust website: https://www.rust-lang.org/tools/install.
  2. Download and run the rustup-init.exe installer.
  3. Follow the on-screen instructions and choose the default options for a standard installation.
  4. Then press 1 for the standard installation.

  Then we can go on to install hdf5:

   choco upgrade chocolatey
   choco install hdf5

  Restart Your Terminal and then check the rustup version by running the following commands:

  rustup --version

• Step_2: Install the virtual environment and the required packages by following commands.

  For PowerShell CLI :

  pyenv local 3.11.3
  python -m venv .venv
  .venv\Scripts\Activate.ps1
  python -m pip install --upgrade pip
  pip install -r requirements.txt

  For Git-bash CLI :

  pyenv local 3.11.3
  python -m venv .venv
  source .venv/Scripts/activate
  python -m pip install --upgrade pip
  pip install -r requirements.txt

Ollama and Deepseek install

🚀 Setup Guide

1️⃣ Create Virtual Environment

python -m venv .venv
source .venv/bin/activate  # Mac/Linux
# OR
source .venv/Scripts/activate  # Windows

2️⃣ Install Dependencies

pip install ollama langchain beautifulsoup4 requests scrapy pandas chromadb faiss-cpu sentence-transformers tiktoken

3️⃣ Install & Run Deepseek LLM

Install Ollama (if not already installed)

curl -fsSL https://ollama.com/install.sh | sh # Mac/Linux

Download Deepseek Model

ollama pull deepseek-r1

Test the model

ollama run deepseek-r1 "What is fake news?"

4️⃣ Quick Test in Python

import ollama

response = ollama.chat(model="deepseek", messages=[{"role": "user", "content": "Analyze this news: The moon landing was fake. How credible is this?"}]) print(response['message']['content'])