Mastering NLP: Tokenization, Sentiment Analysis & Neural MT

Übersicht

Harness the power of language-driven AI with this applied Mastering NLP:

Tokenization, Sentiment Analysis & Neural MT Specialization. Whether you're new to AI or expanding your machine learning expertise, this program guides you through essential and advanced NLP techniques—from sentiment analysis and tokenization to neural translation and transformer models.

You’ll complete three practical courses:

Course 1:

Natural Language Processing Essentials Learn linguistic structures and text preprocessing techniques Apply tokenization, stemming, lemmatization, and POS tagging Explore n-gram models and build basic NLP pipelines Course 2:

Advanced Tokenization and Sentiment Analysis Master advanced tokenization methods like byte-pair encoding Perform NER, emotion classification, and sentiment analysis Build and fine-tune ML models using real-world text data Course 3:

Neural Models and Machine Translation Implement RNNs, LSTMs, GRUs, and Transformer-based models Use pretrained models like BERT, RoBERTa, and MarianMT Train neural machine translation systems with encoder-decoder architecture By the end, you'll be able to:

Design and deploy full NLP applications using classical and neural techniques Tackle real-world language tasks like sentiment prediction and translation Pursue roles in NLP, AI development, and applied machine learning Enroll now to gain hands-on experience in building intelligent, language-aware systems.

Lehrplan

• Course 1: Natural Language Processing Essentials
• Course 2: Advanced Tokenization and Sentiment Analysis
• Course 3: Neural Models and Machine Translation

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Unterrichtet von

Edureka

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Fachgebiete

Computer Science