Last Update: 7/2021
Duration: 4h32m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 1.25 GB
Genre: eLearning | Language: English
Create Word Cloud App Using Streamlit | Sentiment Analysis | Speech to text | Spam Detection | Code Walkthrough
What you'll learn:
You will gain insights on what Natural Language Processing(NLP) is, its Applications & Challenges
You will learn Sentence Segmentation, Word Tokenization, Stemming, Lemmatization, Parsing, POS & Ambiguities in NLP
You will learn to execute using Machine Learning, NLTK & Spacey
You will learn to work with Text Files with Python
You will utilize Regular Expressions for pattern searching in text
You will use Part of Speech Tagging to automatically process raw text files
You will visualize POS and NER with Spacy
You will understand Vocabulary Matching with Spacy
You will use NLTK for Sentiment Analysis
Requirements:
None. (Python is covered extensively in the course)
Description:
Natural Language Processing (NLP) is a very interesting field associated with AI and is at the forefront of many useful applications like a chatbot. Knowledge of NLP is considered a necessity for those pursuing a career in AI. This course covers both the theory as well as the applications of NLP. Case studies are explained along with a walkthrough of the codes for a better understanding of the subject.
A detailed explanation of how to build a web app for NLPusing Streamlit is also explained.
NLP is a subfield of computer science and artificial intelligence concerned with interactions between computers and human (natural) languages. It is used to apply machine learning algorithms to text and speech.
For example, we can use NLP to create systems like speech recognition, document summarization, machine translation, spam detection, named entity recognition, question answering, autocomplete, predictive typing and so on.
Nowadays, most of us have smartphones that have speech recognition. These smartphones use NLP to understand what is said. Also, many people use laptops whose operating system has built-in speech recognition.
Some Examples:
1.Cortana
The Microsoft OS has a virtual assistant called Cortana that can recognize a natural voice. You can use it to set up reminders, open apps, send emails, play games, track flights and packages, check the weather and so on.
2.Siri
Siri is a virtual assistant of the Apple Inc.'s iOS, watchOS, macOS, HomePod, and tvOS operating systems. Again, you can do a lot of things with voice commands: start a call, text someone, send an email, set a timer, take a picture, open an app, set an alarm, use navigation and so on.
3.Gmail
The famous email service Gmail developed by Google is using spam detection to filter out some spam emails.
In this course we will deal with:
a)NLP Introduction:
What is NLP
Applications of NLP
Challenges in NLP
b)Key concepts in NLP:
Sentence Segmentation
Word Tokenization
Stemming
Lemmatization
Parsing
POS
Ambiguities in NLP
c)NLP in Action
NLTK
Sentence Tokenization
Word Tokenization
Stemming
Lemmatization
Noise Removal
Spacy
Parts of Speech Tagging
Dependency Parsing
Spell Correction
Point of View
Regular Expressions
Flash Text
Named Entity Recognition - NER
d)Case studies:
Speech recognition
Sentiment analysis
Word Cloud
Spam detection
You will not only get fantastic technical content with this course, but you will also get access to both our course-related Question and Answer forums, as well as our live student chat channel, so you can team up with other students for projects, or get help on the course content from myself and the course teaching assistants.
All of this comes with a 30-day money back guarantee, so you can try the course risk-free.
What are you waiting for? Become an expert in natural language processing today!
I will see you inside the course,
Who this course is for:
Data Scientists, Python Programmers, ML Practitioners, IT Managers managing data science projects
Python developers interested in learning how to use Natural Language Processing
Download link:
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