Project Title : Personality Prediction System

Objective:
To develop a machine learning-based system that can predict a person’s personality type based on their input data such as text (e.g., social media posts), quiz responses, or behavioral traits.

Technologies Used:

Programming Language: Python

Libraries/Tools: Pandas, scikit-learn, NLTK/spaCy, TensorFlow/Keras (optional)

Techniques: Natural Language Processing (NLP), Classification Algorithms

Dataset: MBTI Personality Dataset (e.g., from Kaggle or social media data)

Approach:

Data Collection:

Use a dataset containing personality types (e.g., MBTI: INFP, ENTP, etc.) and text samples or survey responses

Data Preprocessing:

Clean and preprocess text data (remove stop words, tokenize, lemmatize)

Encode personality types into numerical labels

Extract features using TF-IDF, Bag of Words, or word embeddings

Model Building:

Apply classification algorithms such as:

Logistic Regression

Random Forest

Support Vector Machine (SVM)

Neural Networks (optional for advanced accuracy)

Training & Evaluation:

Train the model on training data

Evaluate using accuracy, precision, recall, F1-score, and confusion matrix

User Interface (Optional):

Develop a web-based quiz or input box using Streamlit or Flask

Let users input text or answer questions to predict their personality

Outcome:
An intelligent system that can predict users’ personality types based on their text or behavior using machine learning, useful for personal development, HR tools, or social apps.