[ FreeCourseWeb ] Udemy - Master Natural Language Processing (NLP) with Python

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[ FreeCourseWeb.com ] Udemy - Master Natural Language Processing (NLP) with Python
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction
    • 1. Introduction-en_US.srt (1.4 KB)
    • 1. Introduction.mp4 (11.3 MB)
    2. Python Programming Using Google Colab
    • 1. Introduction to Colab Google Cloud Development Environment-en_US.srt (8.3 KB)
    • 1. Introduction to Colab Google Cloud Development Environment.mp4 (25.9 MB)
    • 10. Tuple-en_US.srt (5.3 KB)
    • 10. Tuple.mp4 (19.8 MB)
    • 11. Set-en_US.srt (4.8 KB)
    • 11. Set.mp4 (19.6 MB)
    • 12. Dictionary-en_US.srt (2.8 KB)
    • 12. Dictionary.mp4 (13.0 MB)
    • 13. Getting Started with NumPy-en_US.srt (8.7 KB)
    • 13. Getting Started with NumPy.mp4 (28.5 MB)
    • 14. NumPy Shape in Arrays-en_US.srt (4.0 KB)
    • 14. NumPy Shape in Arrays.mp4 (12.7 MB)
    • 15. NumPy Iterating Arrays-en_US.srt (1.5 KB)
    • 15. NumPy Iterating Arrays.mp4 (5.7 MB)
    • 16. NumPy Joining Arrays-en_US.srt (2.8 KB)
    • 16. NumPy Joining Arrays.mp4 (13.4 MB)
    • 17. NumPy Splitting Arrays-en_US.srt (1.7 KB)
    • 17. NumPy Splitting Arrays.mp4 (6.1 MB)
    • 18. NumPy Searching and Sorting Arrays-en_US.srt (2.7 KB)
    • 18. NumPy Searching and Sorting Arrays.mp4 (10.3 MB)
    • 19. Getting Started with Pandas-en_US.srt (7.3 KB)
    • 19. Getting Started with Pandas.mp4 (34.3 MB)
    • 2. Getting Started with Python-en_US.srt (4.6 KB)
    • 2. Getting Started with Python.mp4 (13.7 MB)
    • 20. Pandas Dataframe-en_US.srt (6.4 KB)
    • 20. Pandas Dataframe.mp4 (28.1 MB)
    • 21. Pandas Descriptive Statistics-en_US.srt (3.5 KB)
    • 21. Pandas Descriptive Statistics.mp4 (10.8 MB)
    • 22. Pandas Sorting, Slicing, Flipping, Grouping Data-en_US.srt (7.2 KB)
    • 22. Pandas Sorting, Slicing, Flipping, Grouping Data.mp4 (22.7 MB)
    • 23. Data Visualization using Matplotlib-en_US.srt (8.4 KB)
    • 23. Data Visualization using Matplotlib.mp4 (33.0 MB)
    • 3. Variables-en_US.srt (7.4 KB)
    • 3. Variables.mp4 (24.6 MB)
    • 4. Operators-en_US.srt (5.4 KB)
    • 4. Operators.mp4 (18.8 MB)
    • 5. Conditions-en_US.srt (6.3 KB)
    • 5. Conditions.mp4 (18.3 MB)
    • 6. Loops-en_US.srt (7.3 KB)
    • 6. Loops.mp4 (19.9 MB)
    • 7. Functions-en_US.srt (5.3 KB)
    • 7. Functions.mp4 (15.3 MB)
    • 8. Arrays-en_US.srt (4.0 KB)
    • 8. Arrays.mp4 (20.1 MB)
    • 9. List-en_US.srt (4.5 KB)
    • 9. List.mp4 (15.4 MB)
    3. Key concepts in NLP
    • 1. Key concepts in NLP Sentence Segmentation-en_US.srt (2.7 KB)
    • 1. Key concepts in NLP Sentence Segmentation.mp4 (13.2 MB)
    • 2. Key concepts in NLP Word Tokenization-en_US.srt (1.8 KB)
    • 2. Key concepts in NLP Word Tokenization.mp4 (7.4 MB)
    • 3. Key concepts in NLP Stemming-en_US.srt (1.8 KB)
    • 3. Key concepts in NLP Stemming.mp4 (9.0 MB)
    • 4. Key concepts in NLP Lemmatization-en_US.srt (1.6 KB)
    • 4. Key concepts in NLP Lemmatization.mp4 (6.5 MB)
    • 5. Key concepts in NLP Stop Words-en_US.srt (2.0 KB)
    • 5. Key concepts in NLP Stop Words.mp4 (6.7 MB)
    • 6. Key concepts in NLP Dependency Parsing-en_US.srt (1.3 KB)
    • 6. Key concepts in NLP Dependency Parsing.mp4 (4.6 MB)
    • 7. Key concepts in NLP Parts of Speech-en_US.srt (3.0 KB)
    • 7. Key concepts in NLP Parts of Speech.mp4 (11.2 MB)
    4. Ambiguities in NLP
    • 1. Ambiguities in NLP-en_US.srt (5.6 KB)
    • 1. Ambiguities in NLP.mp4 (17.4 MB)
    5. NLP Libraries and Coding for NLP
    • 1. NLTK and NLP in action-en_US.srt (7.3 KB)
    • 1. NLTK and NLP in action.mp4 (31.8 MB)
    • 2. Noise removal-en_US.srt (1.7 KB)
    • 2. Noise removal.mp4 (9.8 MB)
    • 3. Spacy-en_US.srt (2.5 KB)
    • 3. Spacy.mp4 (11.2 MB)
    • 4. Flash Text-en_US.srt (1.4 KB)
    • 4. Flash Text.mp4 (10.1 MB)
    • 5. Named Entity Recognition (NER)-en_US.srt (2.5 KB)
    • 5. Named Entity Recognition (NER).mp4 (13.3 MB)
    6. Case Studies (with walk through of the codes)
    • 1. Case Study Sentiment Analysis & Word Cloud-en_US.srt (11.1 KB)
    • 1. Case Study Sentiment Analysis & Word Cloud.mp4 (54.1 MB)
    • 2. Case Study Speech to Text deployment in a call center-en_US.srt (9.0 KB)
    • 2. Case Study Speech to Text deployment in a call center.mp4 (37.3 MB)
    • 3. Text Summarization-en_US.srt (3.9 KB)
    • 3. Text Summarization.mp4 (24.4 MB)
    • 4. Case Study 4 Spam Classification Using Machine Learning-en_US.srt (6.6 KB)
    • 4. Case Study 4 Spam Classification Using Machine Learning.mp4 (29.8 MB)
    • Bonus Resources.txt (0.3 KB)

Description

Master Natural Language Processing (NLP) with Python

MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 739 MB | Duration: 2h 43m
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.

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.

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[ FreeCourseWeb ] Udemy - Master Natural Language Processing (NLP) with Python

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Download torrent
739.2 MB
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[ FreeCourseWeb ] Udemy - Master Natural Language Processing (NLP) with Python

Torrent hash: 369D9A2125E972282EECDD6BA6A94D95D0920E18