NLP Text Sentiment Classification w/o training data - Hugging Face Zero-Shot pipeline in Python скачать в хорошем качестве

NLP Text Sentiment Classification w/o training data - Hugging Face Zero-Shot pipeline in Python

Any Machine learning technique requires you to have labelled data to train the model / build a classifier. But a lot of Business have no training or annotated data to efficiently build a Text Classification or Sentiment Classification Model. This new Zero-Shot Classification Pipeline from Hugging Face is a blessing for any such company. All you need to import is hugging face transformers library and use the pipeline `zero-shot-classification` to get your State-of-the-Art (SOTA) Text Classification Model up and running. It also can do Sentiment Classification into Positive and Negative. Extremely easy to use for any programmer. Google Colab (by Joe Davison) - https://colab.research.google.com/dri... Zero-Shot Learning in Modern NLP - https://joeddav.github.io/blog/2020/0... Hugging face 🤗 Transformers - https://github.com/huggingface/transf... Topics: zero-shot classification without annotated data, NLP without training data, NLP Text Classification using Deep Learning, Sentiment Classification using Deep Learning, Python Sentiment Analysis, Python NLP Classification