Mude Jayaprakash has completed
Natural Language Processing (NLP) in Python
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3,550 XP
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Course Description
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!Training 2 or more people?
Get your team access to the full DataCamp platform, including all the features.- 1
Text Processing Fundamentals
FreeLearn 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.
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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.
Bag-of-Words representation50 xpBuilding vocabulary from customer reviews100 xpTransforming text to numbers with BoW100 xpFrequency analysis of product reviews100 xpVisualizing word frequencies100 xpTF-IDF vectorization50 xpTF-IDF representation of product feedback100 xpComparing BoW and TF-IDF representations100 xpEmbeddings50 xpExploring word relationships with embeddings100 xpVisualizing and comparing word embeddings100 xp - 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.
Hugging Face pipelines for sentiment analysis50 xpAnalyzing the sentiment of a review100 xpBatch classifying multiple reviews100 xpComparing models on labeled review data100 xpZero-shot classification and QNLI50 xpZero-shot classification of support tickets100 xpDoes the text answer the question?100 xpQuestion similarity and grammatical correctness50 xpDetecting duplicate questions100 xpChecking grammatical correctness100 xp - 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.
Token classification50 xpIdentifying named entities in news headlines100 xpPart of Speech tagging for text analysis100 xpQuestion answering50 xpAnswering questions from product descriptions100 xpGenerating natural answers with abstractive QA100 xpSequence generation tasks50 xpSummarizing news articles for quick insights100 xpTranslating customer reviews to French100 xpBuilding a search completion system100 xpCongratulations50 xp
Training 2 or more people?
Get your team access to the full DataCamp platform, including all the features.datasets
product_reviews.csvcollaborators
prerequisites
Python Toolbox
Fouad TradMachine Learning Engineer
Fouad is an experienced ML engineer, researcher, and educator, currently pursuing a Ph.D. in applied ML, with a focus on cybersecurity applications. His talent lies in simplifying complex data science concepts, making them accessible to everyone.
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