Named Entity Recognition (NER) & Token Classification

Boost your business's decision-making with our expert services in named entity recognition (NER) and token classification, employing Python, Hugging Face, and spaCy. Our solutions process large volumes of unstructured text data, generating valuable insights for your business.

Our NER services identify and extract relevant entities like names, organizations, locations, and more from unstructured text data. Leveraging our expertise in named entity recognition, you can extract valuable insights from your data and make better decisions for your business.

Token classification, a vital aspect of information extraction, involves labeling tokens in text. Our token classification services analyze text data and uncover relationships between entities, empowering you to make data-driven decisions propelling your business forward.

Example Use Cases

News Article NER with Python, Hugging Face, and SpaCy

News agencies can employ our named entity recognition (NER) services using Python, Hugging Face, and SpaCy to analyze news articles and automatically identify and categorize entities, such as people, locations, and organizations. This can aid in content recommendation, summarization, and the generation of insights for better decision-making.

E-commerce Product Token Classification with BERT and PyTorch

E-commerce platforms can benefit from our token classification services using BERT and PyTorch to analyze product descriptions and automatically identify and categorize entities, such as SKUs, MFRs, MPNs, and quantities. This enables enhanced product search, recommendation, and user sentiment analysis, ultimately leading to better customer experiences and data-driven decision-making processes.

Healthcare Data NER with LSTM-CNNs and Token Classification

Healthcare organizations can leverage our NER with bidirectional LSTM-CNNs and token classification services to analyze medical records and research articles, enabling the automatic identification and categorization of entities such as patient names, symptoms, and treatment-related information. This can assist in decision support, research, and data management, leading to improved patient care and streamlined healthcare processes.

Financial Data Token Classification using NLP and Machine Learning

Financial institutions can employ our NLP and machine learning expertise to perform token classification on financial reports, news articles, and social media content, facilitating the automatic identification of entities like company names, stock symbols, and financial events. This can enhance investment analysis, risk assessment, and compliance, ultimately leading to better-informed financial decisions and optimized operations.

Why Choose Us?

  • Assisting in selecting or creating datasets tailored to your application
  • Guidance in choosing, training, and implementing ML models
  • Expert recommendations for appropriate inference and training hardware
  • Enhancing and optimizing your existing ML workflows
  • Proficiency in Python programming, Machine Learning, NLP, and Deep Learning
  • Delivering high-quality, performance-driven solutions
  • Providing 24/7 support with ongoing assistance after project completion
  • Placing the utmost importance on client satisfaction
  • Years of experience working with diverse clients on a wide array of projects

Technologies Used

Our software services are powered by the following technologies:

  • Python
  • TensorFlow
  • Pandas
  • PyTorch
  • Scikit-learn
  • XGBoost
  • LightGBM
  • CatBoost
  • Gensim
  • FastText
  • OpenCV
  • Gensim
  • TensorFlow
  • Keras
  • NumPy
  • SciPy
  • Statsmodels
  • NLTK
  • spaCy
  • scikit-image
  • Theano
  • Hugging Face Transformers

Contact Us Today

Ready to get started? Contact our team of experts to discuss your token classification needs and discover how our services can help your business thrive. Fill out our contact form or reach out to us directly via phone or email. We look forward to working with you!

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