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Tutorial on AI
spaCy is designed specifically for production use. It helps you build applications that process and “understand” large volumes of text. It can be used to build information extraction or natural language understanding systems, or to pre-process text for deep learning. In this article you will learn about Tokenization, Lemmatization, Stop Words and Phrase Matching operations using spaCy.
spaCy is an open-source Python library that parses and “understands” large volumes of text.
spaCy is the best way to prepare text for deep learning.
It interoperates seamlessly with TensorFlow, PyTorch, scikit-learn, Gensim and the rest of Python’s awesome AI ecosystem.
With spaCy, you can easily construct linguistically sophisticated statistical models for a variety of NLP problems.
It does not matter how much experience you have, actually anybody can start or switch to data science and machine learning. The only important this is, how much eager you are for it. What it means to you. If you are very much keen to work in this field then nobody can stop you. There might be some short term hurdles however if you are focused enough and know your goals regarding where you want to see yourself after certain years, then you will definitely be successful in overcoming those hurdles.
Lot of research is being done in medical field, where researchers are working to develop AI models which can even develop the “Sense of smell”.It will help medical field to detect illness by smelling the human’s breath.They have achieved great success in detecting chemicals called aldehydes. Aldehydes are associated with human illnesses and stress.
NLP can organize unstructured data and perform several automated tasks such as automatic summarization, sentiments analysis, speech recognition, etc.
Data Science Duniya 