├── Chapter01 ├── dividing_sentences_into_words_1.2.ipynb ├── dividing_text_into_sentences_1.1.ipynb ├── lemmatization_1.4.ipynb ├── part_of_speech_tagging_1.3.ipynb └── removing_stopwords_1.5.ipynb ├── Chapter02 ├── counting_nouns_2.1.ipynb ├── dependency_parse_2.2.ipynb ├── entities_and_relations_2.6.ipynb ├── finding_patterns_in_text_2.5.ipynb ├── noun_chunks_2.3.ipynb └── subjects_objects_2.4.ipynb ├── Chapter03 ├── 3.1_simple_classifier.ipynb ├── 3.2_bag_of_words.ipynb ├── 3.3_n_grams.ipynb ├── 3.4_tf_idf.ipynb ├── 3.5_word_embeddings.ipynb ├── 3.6_train_own_word2vec.ipynb ├── 3.7_bert_embeddings.ipynb ├── 3.8_openai_embeddings.ipynb └── 3.9_vector_search.ipynb ├── Chapter04 ├── 4.1_data_preparation.ipynb ├── 4.2_rule_based.ipynb ├── 4.3_unsupervised_classification.ipynb ├── 4.4-svm_classification.ipynb ├── 4.5-spacy_textcat.ipynb └── 4.6_openai_classification.ipynb ├── Chapter05 ├── 5.1_regex.ipynb ├── 5.2_similar_strings.ipynb ├── 5.3_keyword_extraction.ipynb ├── 5.4_named_entity_extraction.ipynb ├── 5.5_training_own_spacy_model.ipynb └── 5.6_fine_tune_bert.ipynb ├── Chapter06 ├── 6.1_topic_modeling_gensim.ipynb ├── 6.2_community_detection.ipynb ├── 6.3-kmeans_with_bert.ipynb ├── 6.4-berttopic.ipynb └── 6.5-contextualized-tm.ipynb ├── Chapter07 ├── 7.1_dependency_parse.ipynb ├── 7.2_parts_of_speech.ipynb ├── 7.3_ner.ipynb ├── 7.4_confusion_matrix.ipynb ├── 7.5_word_clouds.ipynb ├── 7.6_topics_gensim.ipynb └── 7.7_bertopic_vis.ipynb ├── Chapter08 ├── 8.1_Transformers_dataset.ipynb ├── 8.2_Basic_Tokenization.ipynb ├── 8.3_Classification_And_Evaluation.ipynb ├── 8.4_Zero_shot_classification.ipynb ├── 8.5_Transformer_text_generation.ipynb ├── 8.6_Language_Translation_with_transformers.ipynb ├── poetry.lock ├── pyproject.toml └── requirements.txt ├── Chapter09 ├── 9.1_question_answering.ipynb ├── 9.2_QA_on_long_passages.ipynb ├── 9.3_QA_on_document_corpus.ipynb ├── 9.4_abstractive_qa_on_document_corpus.ipynb ├── 9.5_summarization.ipynb ├── 9.6_textual_entailment.ipynb ├── 9.7_explanability_via_classifier.ipynb ├── 9.8_explanability_via_generation.ipynb ├── poetry.lock ├── pyproject.toml └── requirements.txt ├── Chapter10 ├── 10.1_run_basic_llm.ipynb ├── 10.2_instruct_llm.ipynb ├── 10.3_langchain_prompt_with_llm.ipynb ├── 10.4_rag_with_llm.ipynb ├── 10.5_chatbot_with_llm.ipynb ├── 10.6_code_generation_with_llm.ipynb ├── 10.7_generation_and_execute_sql_via_llm.ipynb ├── 10.8_agents_with_llm.ipynb ├── poetry.lock ├── pyproject.toml └── requirements.txt ├── LICENSE ├── README.md ├── Saurabh ├── Gen_AI_and_LLMs.ipynb └── NLU + XAI.ipynb ├── data ├── DataScientist.csv ├── IMDB-Movie-Data.csv ├── IMDB-Movie-Data.json ├── bbc-text.csv ├── bbc_test.json ├── bbc_train.json ├── dep_parse_viz.svg ├── lda-gensim.html ├── music_ner.csv ├── music_ner_bio.bio ├── ner_vis.html ├── questions-words.txt ├── sherlock_holmes.txt ├── sherlock_holmes_1.txt ├── sherlock_mask.png ├── sherlock_wc.png ├── spacy_config.cfg └── spacy_config_ner.cfg 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