Machine-Learning-Application

# Machine Learning Algorithm for Tweet Trend Prediction

## Step 1: Data Collection
- Gathered 50,000 tweets related to the tech industry using Twitter API.
- Data includes timestamps, user information, and tweet content.

## Step 2: Data Preprocessing
- Cleaned data by removing URLs, special characters, and stopwords.
- Applied tokenization and lemmatization to standardize text.

## Step 3: Feature Extraction
- Used TF-IDF to convert text into numerical features.
- Extracted additional features like tweet length and sentiment scores.

## Step 4: Model Training
- Split data into 80% training and 20% testing sets.
- Trained a Random Forest classifier to predict trending topics.

## Step 5: Evaluation
- Achieved 85% accuracy on the test set.
- Model successfully identifies emerging trends in the tech industry.