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[ DevCourseWeb.com ] NLTK: Build Document Classifier & Spell Checker with Python

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Last updated 2/2019
Created by GoTrained Academy,Waqar Ahmed
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 46 Lectures ( 5h 17m ) | Size: 764 MB

NLP with Python - Analyzing Text with the Natural Language Toolkit (NLTK) - Natural Language Processing (NLP) Tutorial

What you'll learn:
NLTK Main Functions: Concordance, Similar, Lexical Dispersion Plot
Text Tokenization
Text Normalization: Stemming & Lemmatization
Text Tagging: Unigram, N-Gram, Regex
Text Classification
Project 1: Gender Prediction Application
Project 2: Document Classification Application
Information Extraction from Text: Chunking, Chinking, Name Entity Recognition
Source Code *.py Files of All Lectures
English Captions for All Lectures
Q&A board to send your questions and get them answered quickly

Requirements:
Good Python level. This Natural Language Processing (NLP) tutorial assumes that you already familiar with the basics of writing simple Python programs and that you are generally familiar with Python's core features (data structures, file handling, functions, classes, modules, common library modules, etc.).
Python 3.4+ (or 2.7). Please note that the tutorial codes are written in Python 3, but it is up to you to fine-tune them if you want to run them on Python 2.

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