Text Mining and Natural Language Processing in Python

Do You Want to Analyse Product Reviews or Social Media Posts to see whether they are positive or negative?

Do you want to be able to make Computers understand Natural Language?

Then this course is just right for you! We will go over the basic, theoretical foundations of Natural Language Processing (NLP) and directly apply them in Python.

It becomes ever more important for companies and organizations to keep track of large amounts of social media posts concerning their brand or product reviews. In NLP there is a whole field called sentiment analysis, that tries to automate this process. In the end, a Deep Learning model can then process a text and predict whether it’s a positive or negative review. If you are curious about how to build such a model, then this course is just right for you!

Get to know the Basics of NLP & Text Mining and learn how to implement it in Python:

My course will help you implement the learned methods directly in Python modules like spaCy or NLTK. Besides learning the ground rules of NLP and common methods, you will even deal with so–called Transformer models, which are state–of–the–art in Natural Language Processing. In the end, you will combine your gained knowledge to build up a functioning Deep Learning Model that can take text as input and predict a sentiment. With this powerful course, you’ll know it all: applying different steps of text preprocessing, combining it in datasets, and building a Deep Learning Model in TensorFlow.