Bilingual NER using BiGRU-CRF
Budget: ₹1,500 – ₹12,500 INR
I am seeking an experienced data scientist or machine learning engineer to develop a named entity recognition (NER) system that can accurately identify and categorize entities in code-mixed text, specifically for Hindi and English languages, using BiGRU-CRF models.
**Key Requirements:**
- The system should be capable of processing data presented in spreadsheets.
- Develop a model using Bidirectional Gated Recurrent Units (BiGRU) combined with a Conditional Random Field (CRF) layer to achieve high accuracy in entity recognition.
- Experience with text processing and machine learning techniques for both English and Hindi languages is essential.
- Solid understanding of NLP techniques and frameworks suitable for handling code-mixed language data.
- Ability to preprocess and clean datasets to fit the model's needs effectively.
**Ideal Skills and Experience:**
- Strong proficiency in Python, specifically with libraries like TensorFlow or PyTorch, pandas, and NumPy.
- Previous experience with NER systems and specifically with dealing with code-mixed language data.
- Knowledge of BiGRU and CRF models, including their implementation and optimization for NLP tasks.
- Experience in handling and analyzing data from spreadsheets for machine learning applications.
- Demonstrable expertise in the evaluation and improvement of model accuracy and efficiency.
The goal of this project is to create a robust NER system that can navigate the complexity of code-mixed text, ensuring accurate entity recognition that can later be utilized for various analytical purposes. If you have a background in NLP and experience with the Hindi and English languages, I encourage you to bid on this project.
**Key Requirements:**
- The system should be capable of processing data presented in spreadsheets.
- Develop a model using Bidirectional Gated Recurrent Units (BiGRU) combined with a Conditional Random Field (CRF) layer to achieve high accuracy in entity recognition.
- Experience with text processing and machine learning techniques for both English and Hindi languages is essential.
- Solid understanding of NLP techniques and frameworks suitable for handling code-mixed language data.
- Ability to preprocess and clean datasets to fit the model's needs effectively.
**Ideal Skills and Experience:**
- Strong proficiency in Python, specifically with libraries like TensorFlow or PyTorch, pandas, and NumPy.
- Previous experience with NER systems and specifically with dealing with code-mixed language data.
- Knowledge of BiGRU and CRF models, including their implementation and optimization for NLP tasks.
- Experience in handling and analyzing data from spreadsheets for machine learning applications.
- Demonstrable expertise in the evaluation and improvement of model accuracy and efficiency.
The goal of this project is to create a robust NER system that can navigate the complexity of code-mixed text, ensuring accurate entity recognition that can later be utilized for various analytical purposes. If you have a background in NLP and experience with the Hindi and English languages, I encourage you to bid on this project.