| Résumé : |
Learn NLP with Python through practical exercises, advanced topics like transformers, and real-world projects such as chatbots and dashboards. A comprehensive guide for mastering NLP techniques.Key FeaturesA comprehensive guide to processing, analyzing, and modeling human language with PythonReal-world projects that reinforce NLP concepts, including chatbot design and sentiment analysisFoundational and advanced NLP techniques for practical applications in diverse domainsBook DescriptionEmbark on a comprehensive journey to master natural language processing (NLP) with Python. Begin with foundational concepts like text preprocessing, tokenization, and key Python libraries such as NLTK, spaCy, and TextBlob. Explore the challenges of text data and gain hands-on experience in cleaning, tokenizing, and building basic NLP pipelines. Early chapters provide practical exercises to solidify your understanding of essential techniques. Advance to sophisticated topics like feature engineering using Bag of Words, TF-IDF, and embeddings like Word2Vec and BERT. Delve into language modeling with RNNs, syntax parsing, and sentiment analysis, learning to apply these techniques in real-world scenarios. Chapters on topic modeling and text summarization equip you to extract insights from data, while transformer-based models like BERT take your skills to the next level. Each concept is paired with Python-based examples, ensuring practical mastery. The final chapters focus on real-world projects, such as developing chatbots, sentiment analysis dashboards, and news aggregators. These hands-on applications challenge you to design, train, and deploy robust NLP solutions. With its structured approach and practical focus, this book equips you to confidently tackle real-world NLP challenges and innovate in the field.What you will learnClean and preprocess text data using Python effectivelyMaster tokenization techniques for words, sentences, and charactersBuild robust NLP pipelines with feature engineering methodsImplement sentiment analysis with machine learning modelsPerform topic modeling using LDA, LSA, and other algorithmsDevelop chatbots and dashboards for real-world applicationsWho this book is forThis book is ideal for students, researchers, and professionals in machine learning, data science, and artificial intelligence who want to master NLP. Beginners will benefit from the step-by-step introduction to text processing and feature engineering, while experienced practitioners can explore advanced topics like transformers and real-world projects. Basic knowledge of Python and familiarity with programming concepts are recommended to fully utilize the content. Enthusiasts with a passion for language technology will also find this guide valuable for building practical NLP applications. |
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