Course curriculum
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1
Introduction
- Introduction to Course
- Introduction to Instructor
- Introduction to Co-Instructor
- Course Introduction
- Links for the Course's Materials and Codes
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2
Introduction(Regular Expressions)
- what is regular expression
- why regular expression
- ELIZA chatbot
- Python regular expression package
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3
Meta Characters(Regular Expressions)
- meta characters
- meta characters_bigBrackets_exercise
- meta characters_bigBrackets_exercise_solution
- meta characters_bigBrackets_exercise_2
- meta characters_bigBrackets_exercise_2_solution
- meta characters_cap
- meta characters_cap_exercise_3
- meta characters_cap_exercise_3_solution
- backSlash
- backSlash_continued
- backSlash_continued 01
- backSlash_Squared_brackets_exercise
- backSlash_Squared_brackets_exercise_solution
- backSlash_Squared_brackets_exercise_another_solution
- backSlash_exercise
- backSlash_exercise_Solution_and_Special Sequences_exercise
- Solution_and_Special Sequences_exercise_solution
- Meta_character_esterics
- Meta_character_esterics_exercise
- Meta_character_esterics_exercise_solution
- Meta_character_esterics_Homework
- Meta_character_esterics_GreedyMatching
- Meta_character_Plus_and_questionMark
- Meta_character_curly_brackets_exercise
- Meta_character_curly_brackets_exercise_solution
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4
Pattern Objects(Regular Expressions)
- pattern_objects
- pattern_objects_match_method_exersize
- pattern_objects_match_method_exersize_solution
- pattern_objects_match_method_vs_search_method
- pattern_objects_finditer_method
- pattern_objects_finditer_method_exersize_solution
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5
More Meta Characters(Regular Expressions)
- meta_characters_logical_or
- meta_characters_beginning_and_end_patterns
- meta_characters_paranthesis
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6
String Modification(Regular Expressions)
- String_modification
- Word_tokenizer_using_split_method
- sub_method_exercise
- sub_method_exercise_solution
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7
Words and Tokens(Text Preprocessing)
- what is a word
- definition of word is task dependent
- Vocabulary and Corpus
- Tokens
- Tokenization in spaCy
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8
Sentiment Classification(Text Preprocessing)
- Yelp_Reviews_classification_mini_project_introduction
- Yelp_Reviews_classification_mini_project_Vocabulary_initialization
- Yelp_Reviews_classification_mini_project_Adding_tokens_to_vocabulary
- Yelp_Reviews_classification_mini_project_look_up_functions_in_vocabulary
- Yelp_Reviews_classification_mini_project_building_vocabulary_from_data
- Yelp_Reviews_classification_mini_project_one_hot_encoding
- Yelp_Reviews_classification_mini_project_one_hot_encoding_implementation
- Yelp_Reviews_classification_mini_project_Encoding_documents
- Yelp_Reviews_classification_mini_project_Encoding_documents_implementation
- Yelp_Reviews_classification_mini_project_train_test_splits
- Yelp_Reviews_classification_mini_project_FeatureComputation
- Yelp_Reviews_classification_mini_project_classification
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9
Language Independent Tokenization(Text Preprocessing)
- Tokenization_in_detial_introduction
- Tokenization_is_hard
- Tokenization_Byte_pair_encoding
- Tokenization_Byte_pair_encoding_example
- Tokenization_Byte_pair_encoding_on_test_data
- Tokenization_Byte_pair_encoding_Implementation_getPairCounts
- Tokenization_Byte_pair_encoding_Implementation_mergeInCorpus
- Tokenization_Byte_pair_encoding_Implementation_BPE_training
- Tokenization_Byte_pair_encoding_Implementation_BPE_encoding
- Tokenization_Byte_pair_encoding_Implementation_BPE_encoding_one_pair
- Tokenization_Byte_pair_encoding_Implementation_BPE_encoding_one_pair
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10
Text Nomalization(Text Preprocessing)
- Word_normalization_CaseFolding
- Word_normalization_Lematization
- Word_normalization_Stemming
- Word_normalization_Sentence_segmentation
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11
String Matching and Spelling Correction(Text Preprocessing)
- Spelling_correction_Minimum_Edit_Distance_intro
- Spelling_correction_Minimum_Edit_Distance_Example
- Spelling_correction_Minimum_Edit_Distance_Table_filling
- Spelling_correction_Minimum_Edit_Distance_Dynamic_programming
- Spelling_correction_Minimum_Edit_Distance_psudoCode
- Spelling_correction_Minimum_Edit_Distance_implementation
- Spelling_correction_Minimum_Edit_Distance_implementation_bugFixing
- Spelling_correction_implementation
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12
Language Modeling
- what is a language model
- language model_formal_definition
- language model_curse_of_dimensionality
- language model_markov_assumption_and_n-grams
- language model_implementation_setup
- language model_implementation_ngrams_function
- language model_implementation_updateCounts_function
- language model_implementation_probabilityModel_funciton
- language model_implementation_readingCorpus
- language model_implementation_samplingText
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13
Topic Modelling with Word and Document Representations
- one hot vectors
- one hot vectors_implementaton
- one hot vectors_limitations
- one hot vectors_uses_as_target_labeling
- term_frequency_for_document_representations
- term_frequency_for_document_representations_implementations
- term_frequency_for_word_representations
- TfIdf_for_document_representations
- TfIdf_for_document_representations_implementation_reading_corpus
- TfIdf_for_document_representations_implementation_computing_document_frequency
- TfIdf_for_document_representations_implementation_computing_tfidf
- TopicModeling_with_TFIDF_1
- TopicModeling_with_TFIDF_3
- TopicModeling_with_TFIDF_4
- TopicModeling_with_TFIDF_5
- Topic_modeling_with_Gensim
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14
Word Embeddings LSI
- wordCoocurrenceMatrix
- wordCoocurrenceMatrix_vs_wordDocumentMatrix
- wordCoocurrenceMatrix_implementation_preparing_data
- wordCoocurrenceMatrix_implementation_preparing_data_2
- wordCoocurrenceMatrix_implementation_preparing_data_gettingVocabulary
- wordCoocurrenceMatrix_implementation_final_function
- wordCoocurrenceMatrix_implementation_handling_memory_issues_on_large_corpus
- wordCoocurrenceMatrix_sparsity
- wordCoocurrenceMatrix_positive_point_wise_mutual_information_PPMI
- PCA_for_dense_embeddings
- Latent_Semantic_Analysis
- Latent_Semantic_Analysis_implementation
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15
Word Semantics
- cosine_similarity
- cosine_similarity_geting_norms_of_vectors
- cosine_similarity_normalizing_vectors
- cosine_similarity_with_more_than_one_vectors
- cosine_similarity_getting_most_similar_words_in_the_vocabulary
- cosine_similarity_getting_most_similar_words_in_the_vocabulary_fixingBug_of_dimensions
- cosine_similarity_word2vec_embeddings
- wordsAnalogies
- wordsAnalogies_implemenation_1
- wordsAnalogies_implemenation_2
- wordsvisualizations
- wordsvisualizations_implementaion
- wordsvisualizations_implementaion_2
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16
Word2vec(Optional)
- static_and_dynamic_embeddings
- self_supervision
- word2vec_algorithm_abstract
- word2vec_why_negative_sampling
- word2vec_what_is_skip_gram
- word2vec_how_to_define_probability_law
- word2vec_sigmoid
- word2vec_formalizing_loss_function
- word2vec_loss_function
- word2vec_gradient_descent_step
- word2vec_implemenation_preparing_data
- word2vec_implemenation_gradient_step
- word2vec_implemenation_driver_function
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17
Need of Deep Learning for NLP(NLP with Deep Learning DNN)
- Why_RNNs_for_NLP
- PyTorch_installation_and_Tensors_intro
- automatic_diffrenciation_pytorch
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18
Introduction(NLP with Deep Learning DNN)
- Why_DNNs_in_machineLearning
- Representational_power_and_data_utilization_capacity_of_DNN
- perceptron
- perceptron_implementation
- DNN_architecture
- DNN_forwardStep_implementation
- DNN_why_activation_function_is_required
- DNN_properties_of_activation_function
- DNN_activation_functions_in_pytorch
- DNN_what_is_loss_function
- DNN_loss_function_in_pytorch
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19
Training(NLP with Deep Learning DNN)
- DNN_Gradient_descent
- DNN_Gradient_descent_implementation
- DNN_Gradient_descent_stochastic_batch_minibatch
- DNN_Gradient_descent_summary
- DNN_implemenation_gradient_step
- DNN_implemenation_Stochastic_gradient_descent
- DNN_implemenation_batch_gradient_descent
- DNN_implemenation_minibatch_gradient_descent
- DNN_implemenation_in_PyTorch
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20
Hyper parameters(NLP with Deep Learning DNN)
- DNN_weights_initializations
- DNN_learning_rate
- DNN_batch_normalization
- DNN_batch_normalization_implementation
- DNN_optimizations
- DNN_dropout
- DNN_dropout_in_pyTorch
- DNN_early_stopping
- DNN_hyperparameters
- DNN_Pytorch_CIFAR10_example
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21
Introduction(NLP with Deep Learning RNN)
- what_is_rnn
- understanding_rnn_with_a_simple_example
- RNN_applications_Human_activity_recognition
- RNN_applications_image_captioning
- RNN_applications_machine_Translation
- RNN_applications_speech_recognition_stock_price_prediction
- RNN_models
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22
Mini-project Language Modelling(NLP with Deep Learning RNN)
- Language_modeling_Next_word_prediction
- Language_modeling_Next_word_prediction_vocabulary_index
- Language_modeling_Next_word_prediction_vocabulary_index_embeddings
- Language_modeling_Next_word_prediction_RNN_architecture
- Language_modeling_Next_word_prediction_Python_1
- Language_modeling_Next_word_prediction_Python_2
- Language_modeling_Next_word_prediction_Python_3
- Language_modeling_Next_word_prediction_Python_4
- Language_modeling_Next_word_prediction_Python_5
- Language_modeling_Next_word_prediction_Python_6
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23
Mini-project Sentiment Classification(NLP with Deep Learning RNN)
- vocabulary_implementation
- vocabulary_implementation_helpers
- vocabulary_implementation_from_file
- Vectorizer
- RNN_setup
- RNN_setup
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24
RNN in PyTorch(NLP with Deep Learning RNN)
- RNN_in_PyTorch_intro
- RNN_in_PyTorch_Embedding_layer
- RNN_in_PyTorch_nn_RNN
- RNN_in_PyTorch_output_shapes
- RNN_in_PyTorch_GatedUnits
- RNN_in_PyTorch_GatedUnits_GRU_LSTM
- RNN_in_PyTorch_bidirectional_RNN
- RNN_in_PyTorch_bidirectional_RNN_output_shapes
- RNN_in_PyTorch_bidirectional_RNN_output_shapes_seperation
- RNN_in_PyTorch_example
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25
Advanced RNN models(NLP with Deep Learning RNN)
- RNN_Encoder_decoder
- RNN_Attention
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26
Neural Machine Translation
- introduction_to_dataset_and_packages
- implementing_language_class
- Testing_language_class_and_implementing_normalization
- reading_dataFile
- reading_building_vocabulary
- EncoderRNN
- DecoderRNN
- DecoderRNN_forward_step
- DecoderRNN_helper_functions
- trainingModule
- Stochastic_Gradient_descent
- NMT_training
- NMT_evaluation