A Complete Natural Language Processing Beginner Masterclass

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A Complete Natural Language Processing Beginner Masterclass™ [TutsNode.com] - A Complete Natural Language Processing Beginner Masterclass 08 Text Preprocessing_ Detailed Step-By-Step Practical Examples
  • 045 Part 8_ Clean Tweets In Dataset.mp4 (233.9 MB)
  • 037 Introducing The Project_ Preprocessing Tweets.en.srt (8.9 KB)
  • 037 Introducing The Project_ Preprocessing Tweets.mp4 (69.2 MB)
  • 038 Coachella-E5-2-DFE.csv (640.8 KB)
  • 038 coachella-tweets.ipynb (256.6 KB)
  • 038 coachella-tweetsComplete.ipynb (282.3 KB)
  • 038 Part 1_ Preprocess Tweets Practical_ Load & Examine Dataset.en.srt (15.2 KB)
  • 038 Part 1_ Preprocess Tweets Practical_ Load & Examine Dataset.mp4 (133.0 MB)
  • 039 Part 2_ Extract Hashtags - Preprocess Tweets Practical.en.srt (5.4 KB)
  • 039 Part 2_ Extract Hashtags - Preprocess Tweets Practical.mp4 (43.6 MB)
  • 040 Part 3_ Remove Usernames, Links, Non-ASCII & Use lower() - Tweets Practical.en.srt (12.1 KB)
  • 040 Part 3_ Remove Usernames, Links, Non-ASCII & Use lower() - Tweets Practical.mp4 (92.1 MB)
  • 041 Part 4_ Try Non-ASCII & Lower Case Functions on Sample Text.en.srt (4.1 KB)
  • 041 Part 4_ Try Non-ASCII & Lower Case Functions on Sample Text.mp4 (23.4 MB)
  • 042 Part 5_ Stopwords Removal.en.srt (10.9 KB)
  • 042 Part 5_ Stopwords Removal.mp4 (45.3 MB)
  • 043 Part 6_ Remove Email Addresses.en.srt (5.7 KB)
  • 043 Part 6_ Remove Email Addresses.mp4 (33.1 MB)
  • 044 Part 7_ Remove Digits & Special Characters.en.srt (12.6 KB)
  • 044 Part 7_ Remove Digits & Special Characters.mp4 (57.3 MB)
  • 045 Part 8_ Clean Tweets In Dataset.en.srt (33.0 KB)
01 Introduction
  • 001 Introduction.en.srt (2.6 KB)
  • 001 Introduction.mp4 (38.4 MB)
02 Intro_ NLP, Data Science & Machine Learning - Are they different_
  • 002 Introducing NLP.en.srt (4.9 KB)
  • 002 Introducing NLP.mp4 (55.6 MB)
  • 003 Data Science In The Real World_ Part 1.en.srt (4.9 KB)
  • 003 Data Science In The Real World_ Part 1.mp4 (41.6 MB)
  • 004 Data Science In The Real World_ Part 2.en.srt (3.6 KB)
  • 004 Data Science In The Real World_ Part 2.mp4 (31.5 MB)
  • 005 NLP In The Real World.en.srt (7.8 KB)
  • 005 NLP In The Real World.mp4 (79.4 MB)
03 NLP Pipeline _Must Watch Section
  • 006 An Overview of NLP Methods.en.srt (5.0 KB)
  • 006 An Overview of NLP Methods.mp4 (34.1 MB)
  • 006 NLP-pipelineSLides.pdf (7.5 MB)
  • 006 NLP-Pipleline-NSS.mp4 (2.4 MB)
  • 007 Text Preprocessing.en.srt (8.5 KB)
  • 007 Text Preprocessing.mp4 (73.8 MB)
  • 008 Text Normalization.en.srt (1.3 KB)
  • 008 Text Normalization.mp4 (11.6 MB)
  • 009 Word Embeddings.en.srt (10.7 KB)
  • 009 Word Embeddings.mp4 (98.4 MB)
  • 010 Build a Model, Transfer Learning, Testing & Evaluating a Model.en.srt (11.1 KB)
  • 010 Build a Model, Transfer Learning, Testing & Evaluating a Model.mp4 (73.3 MB)
04 Why Learn Python for NLP & Data Science_
  • 011 Top Programming Languages Used In Industry 2020.en.srt (9.2 KB)
  • 011 Top Programming Languages Used In Industry 2020.mp4 (82.1 MB)
  • 012 Top Programming Languages Used In Industry 2020 Part 2_ PHP.en.srt (1.9 KB)
  • 012 Top Programming Languages Used In Industry 2020 Part 2_ PHP.mp4 (16.5 MB)
  • 013 Python in Industry 2020.en.srt (4.5 KB)
  • 013 Python in Industry 2020.mp4 (42.4 MB)
  • 014 Python vs R For Data Science & NLP.en.srt (5.5 KB)
  • 014 Python vs R For Data Science & NLP.mp4 (47.7 MB)
05 Google Colab - Setting Up
  • 015 Open A New Colab Notebook.en.srt (1.4 KB)
  • 015 Open A New Colab Notebook.mp4 (15.1 MB)
  • 016 Open .IPYNB Files in Google Colab & Find The Resource Folders For This Course.en.srt (2.5 KB)
  • 016 Open .IPYNB Files in Google Colab & Find The Resource Folders For This Course.mp4 (20.5 MB)
06 Tokenization & Regular Expressions
  • 017 What is Tokenization_ Introduction to the Linguistic theory for tokenization.en.srt (2.3 KB)
  • 017 What is Tokenization_ Introduction to the Linguistic theory for tokenization.mp4 (10.8 MB)
  • 018 Linguistic theory for Word Segmentation.en.srt (3.4 KB)
  • 018 Linguistic theory for Word Segmentation.mp4 (14.4 MB)
  • 019 How To Open The .IPYNB file For The Next Lecture (Optional).en.srt (2.5 KB)
  • 019 How To Open The .IPYNB file For The Next Lecture (Optional).mp4 (20.5 MB)
  • 020 Codealong-TokenizationNLTK.ipynb (2.6 KB)
  • 020 Tokenization with NLTK.en.srt (6.2 KB)
  • 020 Tokenization with NLTK.mp4 (36.4 MB)
  • 020 TokenizationNLTK-complete.ipynb (4.7 KB)
  • 021 Introducing Regular Expressions.en.srt (4.4 KB)
  • 021 Introducing Regular Expressions.mp4 (19.9 MB)
  • 022 Word Segmentation using Python's .split().en.srt (3.1 KB)
  • 022 Word Segmentation using Python's .split().mp4 (19.6 MB)
  • 023 Sentence Segmentation using Python's .split.en.srt (4.5 KB)
  • 023 Sentence Segmentation using Python's .split.mp4 (28.6 MB)
  • 024 Codealong-ReGex.ipynb (6.0 KB)
  • 024 ReGex Split Method re.split() Regular Expressions.en.srt (4.3 KB)
  • 024 ReGex Split Method re.split() Regular Expressions.mp4 (32.9 MB)
  • 025 Regex Substitute Method re.sub Regular Expressions.en.srt (6.1 KB)
  • 025 Regex Substitute Method re.sub Regular Expressions.mp4 (38.2 MB)
  • 026 Search Method using Regex re.search _ Regular Expressions.en.srt (6.0 KB)
  • 026 Search Method using Regex re.search _ Regular Expressions.mp4 (43.3 MB)
  • 027 Part 1_ Find All Emails in Contact Details _ Regular Expressions re.findall().en.srt (6.1 KB)
  • 027 Part 1_ Find All Emails in Contact Details _ Regular Expressions re.findall().mp4 (46.2 MB)
  • 028 Codealong-ReGex-Complete.ipynb (9.7 KB)
  • 028 Part 2_ Find All Emails in Contact Details _ Regular Expressions re.findall().en.srt (6.4 KB)
  • 028 Part 2_ Find All Emails in Contact Details _ Regular Expressions re.findall().mp4 (43.0 MB)
07 Stemming & Lemmatization
  • 029 What is a Stemming_.en.srt (6.5 KB)
  • 029 What is a Stemming_.mp4 (31.9 MB)
  • 030 Stemming with 3 NLTK Methods - Practical.en.srt (14.4 KB)
  • 030 Stemming with 3 NLTK Methods - Practical.mp4 (92.3 MB)

  • Description


    Description

    This course takes you from a beginner level to being able to understand NLP concepts, linguistic theory, and then practice these basic theories using Python – with very simple examples as you code along with me.

    If you are new to Python or any computer programming, the course instructions make it easy for you to code together with me. I explain code line by line.

    The gentle pace takes you gradually from these basics of NLP foundation to being able to understand Mathematical & Linguistic (English-Language based, Non-Mathematical) theories of Deep Learning.

    Natural Language Processing Foundation

    Linguistics & Semantics – study the background theory on natural language to better understand the Computer Science applications

    Pre-processing Data (cleaning)

    Regex, Tokenization, Stemming, Lemmatization

    Part-of-Speech Tagging

    The topics outlined below are taught using practical Python projects!

    Text Classification & Sentiment Analysis

    Unsupervised Sentiment Analysis

    Topic Modelling

    Word Embedding with Deep Learning Models

    LSTM using TensorFlow, Keras Sequence Model

    Speech Recognition

    Convert Speech to Text
    Who this course is for:

    Anyone who is curious about data science & NLP
    Those who are in the Business & Marketing world – learn use NLP to gain insight into customers & products. Can help at interviews & job promotions.
    If you intend to enrol in an NLP/Data Science course but are a total newbie, complete this course before to avoid being lost in class since it can seem overwhelming if classmates already have a foundation in Python or Datascience.

    Requirements

    No previous programming knowledge necessary. The lectures slowly explain the python syntax as you code alone with me.
    New to Python: you get explanations of the code as you code along with me but not only that – theory slides explain concepts to help you understand what’s going on behind the code.
    No data science knowledge required: lectures teach how to work with data and key modelling concepts.
    No NLP knowledge required. Linguistic concepts are taught to give a strong foundation of NLP even before you get into practical coding. This helps you to grasp NLP modelling techniques and cleaning concepts better.



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A Complete Natural Language Processing Beginner Masterclass

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5.6 GB
seeders:19
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A Complete Natural Language Processing Beginner Masterclass

Torrent hash: 936F01FDEA93D0EB565979B460489DFCF215C407