Machine Learning Capstone Project Timeline

Create a Gantt chart starting from 1st December 2023 showcasing the following timeline. The first task is 'Learning Foundations' which lasts for 1-2 weeks involving familiarization with basic machine learning concepts, Python programming, and relevant libraries such as TensorFlow, Scikit-Learn, and understanding basics of natural language processing (NLP). Followed by 'Data Collection and Exploration' for 1 week which includes collection and exploration of a dataset suitable for fake news detection. The third task 'Data Preprocessing' lasts for 2 weeks with focus on text data preprocessing and exploration of TF-IDF feature extraction techniques. The fourth step is 'Model Implementation' which takes 4-6 weeks involving the training of models, hyperparameter tuning, and performance evaluation. The fifth stage 'Ensemble Model' lasts for 2-3 weeks which includes implementation of ensemble model and fine-tuning. Task six is 'Django Integration' executed over 2 weeks to develop a Django web application and integrate the ensemble model into it. Next, 'Real-Time Detection and Optimization', carried out over 2 weeks, works on supporting real-time predictions and optimizing the application for performance. The eighth task, 'Documentation and Presentation', also takes 2 weeks focusing on documenting the process and preparing a presentation summarizing the project. The penultimate stage is 'Review and Feedback' stretching for 1-2 weeks to seek feedback and make necessary adjustments. The timeline ends with 'Final Presentation and Submission' in the last week, presenting the capstone project and submitting the project documentation and any required materials.