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Full Stack AI Developer Roadmap
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Module 9
Natural Language Processing
1
Text Preprocessing Techniques
Preprocess text: tokenization, stopword removal, and lemmatization
2
Text Representation: Bag-of-Words and TF-IDF
Represent text using Bag-of-Words and TF-IDF vectors
3
Text Classification with Traditional ML
Train text classification models using traditional ML techniques
4
Word Embeddings: Word2Vec and GloVe
Explain word embeddings and use pre-trained Word2Vec/GloVe vectors
RNNs and LSTMs for Sequence Classification
Explain RNN/LSTM architecture and implement sequence classification
6
Attention and Transformers Explained
Explain the attention mechanism and Transformer architecture
7
Hugging Face for Text Classification and NER
Use Hugging Face transformers for text classification and NER
8
NLP Evaluation Metrics: A Practical Guide
Explain and apply evaluation metrics for NLP tasks (e.g., perplexity, BLEU, ROUGE)
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Computer Vision with CNNs
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Large Language Models and Generative AI