Master Natural Language Processing with Transformers

Files Included :
1 -Introduction to Course (26.27 MB)
2 -Introduction to NLP (45.88 MB)
3 -Setting Up the Python Environment (15.27 MB)
4 -Installing and Configuring VSCode (11.91 MB)
5 -Installing Essential NLP Packages (45.36 MB)
1 -What is Lower Casing and and Implementation (17.17 MB)
2 -Tokenization Concepts and Coding (35.95 MB)
3 -Handling Punctuation Techniques and Code Examples (25.66 MB)
4 -Processing Chat Words with Coding Examples (30.19 MB)
5 -Handling Emojis Strategies and Code Implementation (24.97 MB)
6 -Stemming Concepts and Coding (32.07 MB)
7 -Lemmatization Concepts and Coding (48.14 MB)
8 -What is Stop Words and Coding (39.06 MB)
9 -Spelling Correction and Coding (24.44 MB)
1 -Bag of Words (78.22 MB)
2 -n-grams (75.26 MB)
3 -One Hot Encoding (55 MB)
4 -Tf-Idf (103.11 MB)
5 -word2vec Introduction (38.88 MB)
6 -word2vec CBOW (89.86 MB)
7 -word2vec CBOW Coding (68.19 MB)
8 -Word2vec Skip gram (27.87 MB)
9 -Pre-Trained Word2Vec Model (47.64 MB)
1 -Introduction to Transformers (24.09 MB)
2 -Understanding Self-Attention Mechanism (63.02 MB)
3 -Multi-Head Attention Explained (38.39 MB)
4 -Position Encoding Concept and Importance (71.89 MB)
5 -Transformer Encoder Architecture (67.42 MB)
6 -Transformer Decoder Part 1 (101.99 MB)
7 -Transformer Decoder Part 2 (83.37 MB)
1 -Introduction to Hugging Face Ecosystem (57.52 MB)
2 -Overview of the BERT Model Architecture (86.19 MB)
3 -Project Building a Sentiment Classification Model Using BERT (164.79 MB)
1 -Overview of the T5 Model and Its Capabilities (58.53 MB)
2 -Project Training a Text Translation Model Using T5 (59.8 MB)
1 -Thank you (27.48 MB)]
Screenshot
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