Datacamp – Natural Language Processing in Python 2024-8

Natural Language Processing in Python, The majority of data is unstructured. This includes information recorded in books, online articles, and audio files. In this track, you’ll gain the core Natural Language Processing (NLP) skills you need to convert that data into valuable insights—from learning how to automatically transcribe TED talks through to identifying whether a movie review is positive or negative. Along the way, you’ll be introduced to popular NLP Python libraries, including NLTK, scikit-learn, spaCy, and SpeechRecognition. By the end of the track, you’ll be ready to transcribe audio files and understand how to extract insights from real-world sources, including Wikipedia articles, online review sites, and data from a flight booking system.

What you’ll learn

• Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.
• Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.
• Learn how to load, transform, and transcribe speech from raw audio files in Python.

Specificatoin of Natural Language Processing in Python

• Publisher : Datacamp
• Teacher : Katharine Jarmul
• Language : English
• Level : All Levels
• Number of Course : 5
• Duration: 20h

Content of Natural Language Processing in Python

Pictures

Sample Clip

Installation Guide

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Subtitle : English

Quality: 720p

Download Links

Feature Engineering for NLP in Python

Download – 73 MB

Introduction to Natural Language Processing in Python

Download – 95 MB

Natural Language Processing with spaCy

Download – 87 MB

Sentiment Analysis in Python

Download – 79 MB

Spoken Language Processing in Python

Download – 67 MB

File size

404 MB