Akhileshwar Reddy Avula

Highly motivated and quick learner with a strong passion for continuous self-improvement and adaptability across diverse environments. Possesses a broad skill set in Computer Science with a keen interest in leveraging knowledge and expertise to seek exciting opportunities for professional growth. Committed to making significant contributions to organizational success through the optimum utilization of skills and knowledge.

Fake Account detection using Machine Learning:

• Objective: Developed a machine learning model to identify fake accounts.
• Methodology:
• Data Collection: Acquired a relevant dataset.
• Data Cleaning: Performed data cleaning to ensure the quality and accuracy of the dataset.
• Data Splitting: Split the dataset into training and test sets.
• Model Training: Trained the model using Naive Bayes Classifier, Decision Tree and Random Forest algorithm.
• Classification and Prediction: Applied the trained model to classify and predict fake accounts.
• Evaluation: Assessed the accuracy of the classifiers.
• Results:
• Achieved approximately 97% accuracy in detecting fake accounts using the Decision Tree algorithm.

Tools and Technologies: Naive Bayes Classifier, Random Forest, Decision Tree algorithm, Python, Data Cleaning techniques.