Abhisek Maharana
Aspiring AI/ML Engineer | 3 years of AI/ML experience through self-driven projects and open-source learning. | Generative AI & MLOps Enthusiast
Fun with AI
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chatbot-using-gemini
This chatbot application uses the Google Gemini model. It features an HTML, CSS, and JavaScript frontend and a Flask backend. Users interact with the chatbot through the interface.
Fake_News_Classifier
The Fake News Classifier is a TensorFlow-based machine learning project that detects and classifies fake news with 97% accuracy. The repository includes a single Python file with complete code for building and training the model, which you can use to create and deploy your own model.
Fine-Tuning-of-BERT-Model
This project fine-tunes the BERT model on Kaggle's spam-ham dataset to classify messages. It explores transformers and large language models (LLMs) in generative AI, with potential for customization to other sentiment analysis tasks. The repository includes a single Jupyter Notebook for complete code on preprocessing, training, and prediction.
Sentiment-Analyzer
The Sentiment Analysis Model is a TensorFlow-based project that predicts text sentiment. Trained on Twitter data, it can be customized with other datasets for personalized sentiment predictions. The repository includes a single Jupyter Notebook with complete code for preprocessing, model training, and prediction.
Whatsapp-Chat-Analyzer
The WhatsApp Chat Analyzer is a data analysis project that provides insights into WhatsApp chats. It analyzes chat data to show metrics like the number of lines, most used letter, chatting duration, media files shared, most used emojis, and group member activity. The results are displayed on a user-friendly dashboard built with Streamlit.
text-to-speech
This project is a text-to-speech web application built using the Microsoft Edge TTS model. The user interface is created with the Gradio framework. Users can input text, set the pitch and speech rate, choose from various voices in the voice library, and download the generated audio file.