Subject – Machine Learning for Natural Language Processing (NLP)
Industry – Machine Learning and AI
Introduction:
Welcome to the eLearning course on “Text Preprocessing and Tokenization” offered by T24Global Company. In this course, we will delve into the fundamental concepts and techniques of text preprocessing and tokenization in the context of Machine Learning and Artificial Intelligence (AI).
Machine Learning and AI have revolutionized the way we process and analyze vast amounts of textual data. However, before feeding the data into machine learning algorithms, it is crucial to preprocess and tokenize the text effectively. Text preprocessing involves transforming raw text into a format that can be easily understood and processed by machine learning models. Tokenization, on the other hand, refers to the process of breaking down text into smaller units, known as tokens, such as words or characters.
This course is designed to provide you with a comprehensive understanding of the various techniques and tools used in text preprocessing and tokenization. By the end of this course, you will be equipped with the knowledge and skills necessary to effectively preprocess and tokenize text data for further analysis and modeling.
The course will begin with an overview of the importance of text preprocessing and tokenization in the field of Machine Learning and AI. We will explore real-world applications where text preprocessing plays a critical role in achieving accurate and meaningful results. Understanding the significance of text preprocessing will set the foundation for the subsequent topics covered in this course.
Next, we will dive into the core concepts of text preprocessing. You will learn about different techniques such as lowercasing, stemming, lemmatization, stop word removal, and noise removal. We will discuss the advantages and limitations of each technique and provide practical examples to illustrate their implementation.
Following that, we will explore the process of tokenization in detail. You will understand the importance of tokenization in text analysis and learn about various tokenization methods, including word-level tokenization, character-level tokenization, and subword-level tokenization. We will discuss the pros and cons of each method and guide you through the implementation process using popular libraries and tools.
Throughout the course, you will have the opportunity to engage in hands-on exercises and coding assignments, allowing you to apply the concepts learned and gain practical experience in text preprocessing and tokenization. Additionally, you will have access to a dedicated discussion forum where you can interact with fellow learners and instructors to seek clarification and share insights.
Whether you are a beginner looking to enter the field of Machine Learning and AI or a professional seeking to enhance your text analysis skills, this course will provide you with a solid foundation in text preprocessing and tokenization. Join us on this exciting journey and unlock the potential of textual data in the world of Machine Learning and AI. Let’s get started!
NOTE – Post purchase, you can access your course at this URL – https://mnethhil.elementor.cloud/courses/text-preprocessing-and-tokenization/ (copy URL)
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Lessons Included