I am Ankit Aglawe, a Machine Learning Engineer based in Manchester, UK. With a master's degree in Artificial Intelligence and over five years of professional experience, I specialize in developing innovative AI solutions. My expertise includes Text Classification, Large Language Models (LLMs), and applications in Financial AI.

1. TextPredict: Advanced Text Prediction Tool
   Documentation
   Developed an advanced text prediction tool that leverages sophisticated language models to generate accurate and contextually appropriate text. This project demonstrates my proficiency in natural language processing and predictive modeling.

2. EmotionClassifier: Emotion Classification Package
   Created a comprehensive package for classifying emotions in text using various pre-trained models. It offers customizable preprocessing, visualization tools, and seamless integration with data platforms, enhancing sentiment analysis capabilities in diverse applications.

3. SentimentPredictor: Sentiment Analysis Package
   Developed a flexible sentiment analysis package supporting multiple pre-trained models. Features include customizable preprocessing, visualization tools, fine-tuning capabilities, and integration with pandas DataFrames, facilitating efficient sentiment analysis workflows.

4. ConfigConverter: Configuration File Converter
   Documentation
   Designed a tool to convert configuration files between different formats, aiding in the management and migration of application settings across various environments. This utility simplifies configuration management in complex systems.

• How to Perform Sentiment Analysis on Reviews Using a Fine-Tuned RoBERTa Model
  Authored a detailed guide on performing sentiment analysis using a fine-tuned RoBERTa model, providing insights into model fine-tuning and practical applications in sentiment analysis.

• How to Perform Emotion Classification on Text Using a Fine-Tuned DeBERTa Model
  Wrote a comprehensive article on emotion classification utilizing a fine-tuned DeBERTa model, discussing methodologies and implementation strategies for effective emotion detection.

• Categorized Text Reviews Dataset
  Compiled a comprehensive dataset of categorized text reviews for various natural language processing tasks, supporting research and development in sentiment analysis and text classification.

• RoBERTa Base Sentiment Analysis Model
  Developed a fine-tuned RoBERTa model for sentiment analysis on text reviews, enhancing accuracy and performance in sentiment detection applications.

• DeBERTa v3 Small Base Emotions Classifier
  Created an emotion classification model fine-tuned on diverse text data, enabling nuanced emotion detection in natural language processing tasks.

• DeBERTa XLarge Base Emotions Classifier
  Developed an advanced emotion classification model for detailed emotion analysis, suitable for applications requiring high precision in emotion detection.

• Reviews RoBERTa Sentiment Analyzer (Hugging Face Space)
  Established an interactive space for performing sentiment analysis on text reviews using the fine-tuned RoBERTa model, facilitating hands-on experimentation and application.

I am open to collaboration opportunities and discussions on innovative AI ideas. Connect with me on LinkedIn and explore my other projects on GitHub.