Courses
Natural Language Processing (NLP) in Python
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อัปเดตแล้ว 07/2568เริ่มเรียนหลักสูตรฟรี
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PythonArtificial Intelligence4 ชม.13 videos42 Exercises3,550 เอ็กซ์พี5,992คำแถลงแสดงความสำเร็จ
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Build a Strong NLP Foundation
Unlock the power of Natural Language Processing (NLP) and take your text analysis skills to the next level! This course equips you with essential tools to process, analyze, and extract insights from text data. Start with the fundamentals of text processing, from tokenization to cleaning and normalizing text by removing stop words, punctuation, and applying lemmatization and stemming to improve text consistency.Extract Meaningful Features from Text
Go beyond raw text and transform it into numerical representations! Explore the Bag-of-Words representation, dive into TF-IDF vectorization, and leverage powerful word embeddings like Word2Vec and GloVe to capture semantic relationships between words.Classify and Generate Text with AI
Harness the power of state-of-the-art transformer models using Hugging Face pipelines. Learn how to perform sentiment analysis, classify content, analyze question-answer relationships, assess grammatical acceptability, and generate text using various models. Explore Named Entity Recognition (NER), Part-of-Speech (PoS) tagging, text summarization, and translation to expand your NLP toolkit.Master key NLP libraries
By the end of this course, you’ll have a strong grasp of NLP fundamentals and hands-on experience with key libraries such as nltk, sklearn, gensim, and Hugging Face’s transformers. Start your journey today and transform the way you interact with text data!ข้อกำหนดเบื้องต้น
Python Toolbox1
Text Processing Fundamentals
Learn the essentials of text processing in Natural Language Processing (NLP). Master techniques such as tokenization, stop word and punctuation removal, and text normalization with lowercasing, stemming, and lemmatization to prepare text data for further analysis and insight extraction.
2
Feature Extraction from Text
Transform raw text into powerful numerical features. Create Bag-of-Words and TF-IDF representations to capture word importance across documents, then explore word embeddings like Word2Vec and GloVe to uncover deep semantic patterns. Visualize frequency, relevance, and similarity to bring your text data to life.
3
Text Classification with Hugging Face
Harness the power of pre-trained models to perform advanced text classification tasks. Use Hugging Face pipelines for sentiment analysis, topic classification, and natural language inference. Evaluate semantic similarity and grammatical correctness with state-of-the-art models, all without building anything from scratch.
4
Token Classification and Text Generation
Dive into the core of modern NLP applications with token classification and text generation techniques. Learn to extract meaningful entities and grammatical structures using NER and PoS tagging. Master both extractive and abstractive question answering, and explore advanced generation tasks including summarization, translation, and language modeling using Hugging Face pipelines.
Natural Language Processing (NLP) in Python
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