AI Agent Capabled Chatbot(under construction)

About this AI Agents

AI agents are autonomous systems that perceive their environment, process information, make decisions, and take actions to achieve specific goals—often with minimal human intervention. Unlike simple chatbots that react to user input, AI agents proactively plan and execute multi-step tasks, using tools, data, and reasoning to solve complex problems.
The model used for prediction here is Logistic Regression. Among several models such as Logistic Regression, Decision Tree, Support Vector Machine, Random Forest, K-Nearest Neighbor, Naive Bayes, LightGBM, XGBoost. The dataset was imbalanced, So we used a popular oversampling method called SMOTE to reduce that effect and trained our models with the new balanced dataset. After that Logistic Regression outperformed all the models. If you are interested please visit this link to see the full analysis.
Github link

Preformatted

i = 0;
          while (!deck.isInOrder()) {
          print 'Iteration ' + i;
          deck.shuffle();
           i++;
          }
          print 'It took ' + i + ' iterations to sort the deck.';