Natural Language Processing: Linguistic Features Using NLTK & spaCy

Without fundamental building blocks and industry-accepted tools it is difficult to achieve state-of-art analysis in NLP. In this course you will learn about linguistic features such as word corpora tokenization stemming lemmatization and stop words and understand their value in natural language processing. Begin by exploring NLTK and spaCy two of the most widely used NLP tools and understand what they can help you achieve. Learn to recognize the difference between these tools and understand the pros and cons of each. Discover how to implement concepts like part of speech tagging named entity recognition dependency parsing n-grams spell correction segmenting sentences and finding similar sentences. Upon completion of this course you will be able to build basic NLP applications on any raw language data and explore the NLP features that can help businesses take actionable steps with this data.