Natural Language Processing For Text Analysis With spaCy

Natural Language Processing For Text Analysis With spaCy
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Price: 189.99$

Natural Language Processing (NLP) is a subfield of Artificial Intelligence (AI) to enable computers to comprehend spoken and written human language. NLP has several applications, including text-to-voice and speech-to-text conversion, chatbots, automatic question-and-answer systems (Q & A), automatic image description creation, and video subtitles. With the introduction of Chat GPT, NLP will become more and more popular, potentially leading to increased employment opportunities in this branch of AI. The Spa Cy framework is the workhorse of the Python NLP ecosystem owing to (a) its ability to process large text datasets, (b) information extraction, (c) pre-processing text for subsequent use in AI models, and (d) Developing production-level NLP applications. IFYOUAREANEWCOMERTONLP, ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT NATURALLANGUAGEPROCESSING (NLP) ANDTO DEVELOPNLPMODELSUSINGSPACYThe course is divided into three main parts: Section 1-2: The course will introduce you to the primary Python concepts you need to build NLP models, including getting started with Google Colab (an online Jupyter implementation which will save the fuss of installing packages on your computers). Then the course will introduce the basic concepts underpinning NLP and the spa Cy framework. By this end, you will gain familiarity with NLP theory and the spa Cy architecture. Section 3-5: These sections will focus on the most basic natural language processing concepts, such as: part-of-speech, lemmatization, stemming, named entity recognition, stop words, dependency parsing, word and sentence similarity and tokenization and their spa Cy implementations. Section 6: You will work through some practical projects to use spa Cy for real-world applications An extra section covers some Python data science basics to help you. Why Should You Take My Course?MY COURSE IS A HANDS-ON TRAINING WITH REAL PYTHONSOCIALMEDIAMINING-You will learn to carry out text analysis and natural language processing (NLP) to gain insights from unstructured text data, including tweets. My course provides a foundation to conduct PRACTICAL, real-life social media mining. By taking this course, you are taking a significant step forward in your data science journey to become anexpert in harnessing the power of text for deriving insights and identifying trends. I have an MPhil (Geography and Environment) from the University of Oxford, UK. I also completed a data science intense Ph D at Cambridge University (Tropical Ecology and Conservation). I have several years of experience analyzing real-life data from different sources, including text sources, producingpublications for international peer-reviewed journals and undertaking data science consultancy work. In addition to all the above, youll have MY CONTINUOUS SUPPORTto ensure you get the most value out of your investment! ENROLL NOW:)

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