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An Introduction To Word Vectorization

SynopsisAn Introduction To Word Vectorization, available at Free, wit...
An Introduction To Word Vectorization No.1

An Introduction To Word Vectorization, available at Free, with 5 lectures, and has 134 subscribers.

You will learn about What is Word Vectorization and Why Do We Need It? How to Evaluate and Visualize the Word Vectors, and How to Use Them for Various NLP Tasks? Frequency-Based Methods Prediction-Based Methods This course is ideal for individuals who are This course is designed for anyone who wants an introduction and hands on walkthrough to word vectorization It is particularly useful for This course is designed for anyone who wants an introduction and hands on walkthrough to word vectorization.

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Summary

Title: An Introduction To Word Vectorization

Price: Free

Number of Lectures: 5

Number of Published Lectures: 5

Number of Curriculum Items: 5

Number of Published Curriculum Objects: 5

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

  • What is Word Vectorization and Why Do We Need It?
  • How to Evaluate and Visualize the Word Vectors, and How to Use Them for Various NLP Tasks?
  • Frequency-Based Methods
  • Prediction-Based Methods

    • Who Should Attend

  • This course is designed for anyone who wants an introduction and hands on walkthrough to word vectorization

    • Target Audiences

  • This course is designed for anyone who wants an introduction and hands on walkthrough to word vectorization

    • Word Vectorization: Learn how to transform text into numerical vectors that can be used for various natural language processing (NLP) tasks. In this course, you will learn about the theory and practice of word vectorization, a technique that converts words into numerical vectors that capture some aspects of their meaning, usage, or context. You will learn about the different types of word vectorization methods, such as frequency-based and prediction-based methods, and how they differ in their assumptions, advantages, and disadvantages. You will also learn how to implement some of the word vectorization methods using Python and popular libraries, such as Gensim and TensorFlow, and how to use them for your own NLP projects. You will also learn how to evaluate and visualize the word vectors, and how to use them for various NLP tasks, such as sentiment analysis, text classification, and machine translation.

    The course is divided into the following lectures:

  • Lecture 1: Introduction to Word Vectorization. In this lecture, you will learn about the basics of word vectorization, and why it is important for NLP. You will also learn about the two main categories of word vectorization methods: frequency-based and prediction-based methods, and how they work at a high level.

  • Lecture 2: Frequency-based Methods of Word Vectorization. In this lecture, you will learn about the frequency-based methods of word vectorization, such as one-hot encoding, count vectorizer, TF-IDF, and n-grams. You will see how they work, and what are their advantages and disadvantages. You will also learn how to implement them using Python and Gensim.

  • Lecture 3: Prediction-based Methods of Word Vectorization. In this lecture, you will learn about the prediction-based methods of word vectorization, such as word2vec, fastText, and GloVe. You will see how they work, and what are their advantages and disadvantages. You will also learn how to implement them using Python and TensorFlow.

  • Lecture 4: Evaluation and Visualization of Word Vectors. In this lecture, you will learn how to evaluate and visualize the word vectors, and how to use them for various NLP tasks. You will learn about the different evaluation methods, such as intrinsic and extrinsic evaluation, and the different dimensionality reduction techniques, such as PCA and t-SNE. You will also learn how to use the word vectors for sentiment analysis, text classification, and machine translation.

    • Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Introduction

    Lecture 2: Frequency-Based Methods of Word Vectorization

    Lecture 3: Prediction-Based Methods of Word Vectorization

    Lecture 4: How to Evaluate and Visualize the Word Vectors

    Lecture 5: Hands On With Word2Vec

    Instructors

  • An Introduction To Word Vectorization No.2
    Richard Aragon
    I am still under development

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