Have you ever wondered how big companies like Google, Amazon or Facebook work with textual data? Natural Language Processing is one of the most exciting fields in Data Science and Analytics nowadays. The ability to make a computer understand words and phrases is a technological innovation that brought a huge transformation to tasks such as Information Retrieval, Translation or Text Classification. In this course we are going to learn the fundamentals of working with Text data in Python and discuss the most important techniques that you should know to start your journey in Natural Language Processing. This course was designed for absolute beginners - meaning that everything regarding NLP that we are going to speak in the course will be explained during the lectures, assuming that the student does not have any prior knowledge in the subject.
Learn how to pre-process your text data and build topic modeling, text summarization and sentiment analysis applications New Created by Dr. Ali Feizollah English English [Auto] PREVIEW THIS COURSE - GET COUPON CODE Description Text mining and Natural Language Processing (NLP) are among the most active research areas. Pre-processing your text data before feeding it to an algorithm is a crucial part of NLP. In this course, you will learn NLP using natural language toolkit (NLTK), which is part of the Python. You will learn pre-processing of data to make it ready for any NLP application. We go through text cleaning, stemming, lemmatization, part of speech tagging, and stop words removal.
The abundance of knowledge and resources can be at times overwhelming specifically when you are talking about new age technologies like Natural Language Processing or what we popularly call it as NLP. When trying to educate yourself, you should always choose resources with solid base and fresh books to impart unprecedented package of learnings. Here is the list of top books that can help you expand your NLP knowledge. One of the most widely referenced and recommended NLP books, written by Stanford University professor Dan Jurafsky and University of Colorado professor James Martin, provides a deep-dive guide on the subject of language processing. It's intended to accompany undergraduate or advanced graduate courses in Natural Language Processing or Computational Linguistics. However, it's a must-read for anyone diving into the theory and application of language processing as they grow and strengthen their analytics capabilities.
In this course, we will discuss Azure Machine Learning in detail. You will learn what features it provides and how it is used. We will explore how to process some real-world datasets and find some patterns in that dataset. This course teaches you how to design, deploy, configure and manage your machine learning models with Azure Machine Learning. The course will start with an introduction to the Azure ML toolset and features provided by it and then dive deeper into building some machine learning models based on some real-world problems 4. Data Visualization with Python: The Complete Guide Data Visualization with Python: The Complete Guide.