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[NLP] Python text analysis and natural language processing through IMDB movie review sentiment analysis

This is a class that will provide basic theory and practice of natural language processing through the IMDB movie review sentiment analysis competition on Kaggle.

(4.6) 41 reviews

2,762 learners

  • todaycode
Python
NLP

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What you will learn!

  • Natural Language Processing (NLP)

  • Text data preprocessing (normalization, tokenization, stemming, morphological analysis, stem extraction, phonetic notation)

  • Text data visualization techniques (Matplotlib, Seaborn), Machine learning (Scikit-learn)

  • Deep Learning/Machine Learning, Data Analysis

  • Simple Perceptron Implementation Using Python Standard Library

  • Online Learning, Vowpal Wabbit Concept

  • Various text data vectorization techniques (Bag of Words, n-gram, TF-IDF, Word2Vec)

  • Optimize performance through pipeline implementation

  • Ensemble (Random Forest) and Boosting (Xgboost) Techniques

Machine Learning Sentiment Analysis in Movie Reviews 🎞️
From data preprocessing to evaluation and prediction!

Natural language processing theory and practice
Want to learn all at once? 👩‍💻

This lecture is a class that covers the basic theories and practices necessary for natural language processing through the IMDB movie review sentiment analysis competition on Kaggle. Natural language processing is widely used in chatbots, text analysis, and data preprocessing when developing machine learning/deep learning models.

It covers natural language processing, but it also covers data preprocessing, various machine learning techniques, and deep learning techniques, and it also looks at how to utilize supervised learning and unsupervised learning. In addition to the basic tutorials on Kaggle, it will additionally cover text data visualization, preprocessing, and performance improvement through parallel processing through pipelines. Let's challenge together?

Check out the lecture tutorial first!

This lecture
Helpful people 🔍

complicated
From text data
To find meaning
The person who does it

For development
Natural language processing
Want to learn
Chatbot Developer

Required for sentiment analysis
Various techniques
Want to learn
Data Analyst

Machine learning/deep learning,
NLP etc.
Easy and fun
For those who want to get started


If you listen to the lecture
What can you do? 📌

You can learn classification techniques of machine learning through IMDB movie review data. You will learn how to utilize supervised and unsupervised learning of machine learning . For supervised learning, you will learn sentiment analysis through machine learning, and for unsupervised learning, you will learn dimension reduction and clustering techniques.

  • Natural Language Processing (NLP: Neuro-Linguistic Programming)
  • Text data preprocessing (normalization, tokenization, stemming, morphological analysis, stem extraction, phonemic notation)
  • Data Analysis
  • Text data visualization techniques (Matplotlib, Seaborn)
  • Machine Learning (Scikit-learn) and Deep Learning
  • Simple Perceptron Implementation Using Python Standard Library
  • Online Learning, Vowpal Wabbit Concept
  • Various text data vectorization techniques (Bag of Words, n-gram, TF-IDF, Word2Vec)
  • Optimizing performance through pipeline implementation
  • Ensemble (Random Forest) and Boosting (Xgboost) techniques

📣 Please check before taking the class!

  • We recommend taking the course in an environment with 4GB or more of memory and a dual-core or higher CPU .
  • If your device's performance is a bit lacking because text data preprocessing takes a long time, please practice through the Google Colaboratory link at the bottom of the video!

Created this course
If you are curious about the knowledge sharer? 👩‍💻

Knowledge Sharer Park Jo-eun X Inflearn Interview

Recommended for
these people

Who is this course right for?

  • Anyone who wants to find meaning from complex text data

  • Chatbot developers, data analysts, machine learning, deep learning beginners

Need to know before starting?

  • Python Pandas Data Analysis

  • Machine Learning/Deep Learning Basics

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Curriculum

All

17 lectures ∙ (3hr 30min)

Published: 
Last updated: 

Reviews

All

41 reviews

4.6

41 reviews

  • crecengu님의 프로필 이미지
    crecengu

    Reviews 1

    Average Rating 5.0

    5

    76% enrolled

    선생님 강의 잘 보고 있습니다. 이번에 영화 분석 강의 수강 하려고 하는데, 강의 자료는 어디서 받을 수 있을까요~?

    • 주재홍님의 프로필 이미지
      주재홍

      Reviews 8

      Average Rating 5.0

      5

      65% enrolled

      친절한 설명 좋네요

      • Youngmin Kim님의 프로필 이미지
        Youngmin Kim

        Reviews 7

        Average Rating 5.0

        5

        100% enrolled

        자세한 설명과 예제와 리소스, 첨부 등으로 강의보다 훨씬 더 많은 것을 얻어가는 듯 합니다. 감사합니다.

        • 나대엽님의 프로필 이미지
          나대엽

          Reviews 10

          Average Rating 5.0

          5

          100% enrolled

          감사합니다.

          • 피넛버터제임이님의 프로필 이미지
            피넛버터제임이

            Reviews 3

            Average Rating 4.0

            4

            100% enrolled

            초심자가 듣기에는 조금 어렵지만 유익했습니다!

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