English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 2 Hours | 0.97 GB
learn how to process text, utilize nlp algorithms, and bring all of that knowledge together by doing a case study!
This course is for beginners to Natural Language Processing. The programming language utilized is Python. This is not a programming course, therefore, understanding of Python (beginner to intermediate level) is required prior to taking this course. Consider Python knowledge a pre-requisite to taking this course.
Veysel and Ermin will take you through the whole process. They will show you how to install the required software, introduce you to what NLP is, show you the process/steps/techniques of processing text, go over some of the main algorithms/techniques utilized in NLP, and we will bring a lot of the concepts together through a case study.
The content is not the only reason to register for this course. Veysel has years of experience in this space and can answer any questions you may have. You can do that in the Q and A section of the course. He regularly consults major corporations/businesses in this area.
What Will I Learn?
- perform text pre-processing through tokenization, stemming, lemmatization, pos tagging, named entity recognition
- utilize the most relevant algorithms/techniques in NLP
- identify document similarity
Table of Contents
Introduction to the course
1 IntroWhat You Will Learn
2 Installing Python
3 Jupyter Notebook Intro
4 Natural Language Processing Foundations
5 Python NLP Libraries and Packages
Text Processing and NLP Techniques
6 Installing, Importing, and Viewing NLTK Package
7 Tokenization
8 Stemming and Lemmatization
9 Part-of-Speech Tagging (POS Tagging)
10 Named Entity Recognition
NLP Techniques and Algorithms
11 N-grams
12 Bag of Words – Term Frequency
13 word2vec
14 Topic Modeling (LDA)
Case Studies
15 Document Similarity
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