What you would learn in Text Mining and Natural Language Processing in Python course?
Are You Looking to Study reviews of products or Social Media Posts to determine if the reviews are either positive or negative?
Do you wish to create a system that lets Computers recognize Natural Language?
This course is perfect for you! We will review the fundamental theoretical and conceptual concepts in Natural Language Processing (NLP) and apply them directly in Python.
It's becoming more and more crucial for organizations and companies to track massive amounts of social media content that pertain to their products or brands. In NLP, there's an entire field of study known as sentiment analysis that attempts to automatize the process. The Deep Learning model can then analyze a text and determine whether it's positive or negative. If you're interested in constructing this kind of model, this course is perfect for you!
Learn the basics of NLP & Text Mining and discover the best ways to use it using Python:
My course will guide you through implementing the techniques you've learned using Python modules such as spaCy and NLTK. In addition to learning the fundamentals of NLP and other standard techniques, you can also work with what are known as Transformer models, which are the most advanced technology in Natural Language Processing. At the end of the course, you'll use the knowledge you have gained to create a functional Deep Learning Model that can utilize text input to predict the sentiment. Through this course, you'll be able to master how to apply different stages of text preprocessing, including it with datasets, and then create the Deep Learning Model in TensorFlow.
Take lessons from an expert Machine Learning Engineer as well as a University Professor:
I'm Niklas Lang. I am a Machine-Learning Engineer currently employed by a German IT System House. I've worked on various kinds of textual information generated from our online store description of products reviews on the internet that we transform into highly effective and operational Machine Learning models. In addition, I have taught classes at the university level in Data Science and Business Intelligence.
Here's what you'll get:
A brief introduction Jupyter Notebooks, Python Modules Management, and Notebooks
An Introduction to Natural Languages and NLP Applications
In-Detail Text Preprocessing Techniques for Text Preprocessing in Python
An overview of Feature Engineering Methodologies such as Word2Vec, Bag of Words, or BERT Embeddings
In-Depth Description of Convolutional Neural Networks to Classify Tasks
Incorporating Machine Learning Model for Sentiment Analysis Task in TensorFlow
Learning about the process of Creating, Compiling and Training a Deep-Learning Model in Python
Participants will be able to download Jupyter Notebook and manage Python Modules.
The definition of Natural Language and its Applications
Learn about the Basics of Natural Language Processing
Learn the basics in Text Processing with NLTK and spaCy
Learn about Traditional Feature Engineering Models
Create a Sentiment Analysis Model
Learn to code all these things in Python
Download Text Mining and Natural Language Processing in Python from below links NOW!
Write your comment!
Access Permission Error
You do not have access to this product!
Dear User! To download this file(s) you need to purchase this product or subscribe to one of our VIP plans.