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Udemy - Natural Language Processing (NLP) in Python with 8 Projects [TP]

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Category Other
Added Thursday 1st June 2023 07:09:06 PM (3 years ago)
Size4.7 GB
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Torrent Files (196)
FilenameSize
01 - Welcome/001 Course Overview.mp435.4 MB
01 - Welcome/001 Course Overview_en.vtt4.0 KB
01 - Welcome/002 Reviews UPDATE.mp45.4 MB
01 - Welcome/002 Reviews UPDATE_en.vtt1.6 KB
01 - Welcome/003 Introduction to NLP.mp4133.5 MB
01 - Welcome/003 Introduction to NLP_en.vtt7.4 KB
01 - Welcome/004 Course FAQs.html1.6 KB
02 - Installation & Setup/001 Course Installation.mp481.1 MB
02 - Installation & Setup/001 Course Installation_en.vtt12.2 KB
02 - Installation & Setup/002 Local Installation Steps.html860 bytes
02 - Installation & Setup/003 Links to Notebooks (As taught in Lectures).html3.3 KB
02 - Installation & Setup/004 Links to Notebooks (More explanatory notebook for refrence).html3.4 KB
02 - Installation & Setup/24056952-requirements.txt12 bytes
02 - Installation & Setup/external-assets-links.txt99 bytes
03 - Basics of Natural Language Processing/001 Section _ Introduction.mp449.0 MB
03 - Basics of Natural Language Processing/001 Section _ Introduction_en.vtt2.8 KB
03 - Basics of Natural Language Processing/002 Tokenization Basic Part - 1.mp473.1 MB
03 - Basics of Natural Language Processing/002 Tokenization Basic Part - 1_en.vtt9.8 KB
03 - Basics of Natural Language Processing/003 Tokenization Basic Part - 2.mp450.3 MB
03 - Basics of Natural Language Processing/003 Tokenization Basic Part - 2_en.vtt8.4 KB
03 - Basics of Natural Language Processing/004 Tokenization Basic Part - 3.mp412.7 MB
03 - Basics of Natural Language Processing/004 Tokenization Basic Part - 3_en.vtt3.2 KB
03 - Basics of Natural Language Processing/005 Stemming & Lemmatization - 1.mp426.8 MB
03 - Basics of Natural Language Processing/005 Stemming & Lemmatization - 1_en.vtt6.6 KB
03 - Basics of Natural Language Processing/006 Stemming & Lemmatization - 2.mp423.5 MB
03 - Basics of Natural Language Processing/006 Stemming & Lemmatization - 2_en.vtt4.9 KB
03 - Basics of Natural Language Processing/007 Stop Words.mp432.7 MB
03 - Basics of Natural Language Processing/007 Stop Words_en.vtt6.7 KB
03 - Basics of Natural Language Processing/008 Vocabulary and Matching Part - 1.mp484.4 MB
03 - Basics of Natural Language Processing/008 Vocabulary and Matching Part - 1_en.vtt9.7 KB
03 - Basics of Natural Language Processing/009 Vocabulary and Matching Part - 2 (Rule Based).mp472.8 MB
03 - Basics of Natural Language Processing/009 Vocabulary and Matching Part - 2 (Rule Based)_en.vtt8.8 KB
03 - Basics of Natural Language Processing/010 Vocabulary and Matching Part - 3 (Phrase Based).mp433.1 MB
03 - Basics of Natural Language Processing/010 Vocabulary and Matching Part - 3 (Phrase Based)_en.vtt4.0 KB
03 - Basics of Natural Language Processing/011 Parts of Speech Tagging.mp455.7 MB
03 - Basics of Natural Language Processing/011 Parts of Speech Tagging_en.vtt8.0 KB
03 - Basics of Natural Language Processing/012 Named Entity Recognition.mp482.9 MB
03 - Basics of Natural Language Processing/012 Named Entity Recognition_en.vtt12.9 KB
03 - Basics of Natural Language Processing/013 Sentence Segmentation.mp452.9 MB
03 - Basics of Natural Language Processing/013 Sentence Segmentation_en.vtt9.0 KB
03 - Basics of Natural Language Processing/external-assets-links.txt226 bytes
04 - Project 1 _ Spam Message Classification/001 Business Problem & Dataset.mp442.6 MB
04 - Project 1 _ Spam Message Classification/001 Business Problem & Dataset_en.vtt8.0 KB
04 - Project 1 _ Spam Message Classification/002 Data Exploration & Preprocessing.mp450.3 MB
04 - Project 1 _ Spam Message Classification/002 Data Exploration & Preprocessing_en.vtt9.5 KB
04 - Project 1 _ Spam Message Classification/003 Split Data in Training & Testing.mp440.2 MB
04 - Project 1 _ Spam Message Classification/003 Split Data in Training & Testing_en.vtt6.8 KB
04 - Project 1 _ Spam Message Classification/004 Apply Random Forest.mp463.9 MB
04 - Project 1 _ Spam Message Classification/004 Apply Random Forest_en.vtt12.0 KB
04 - Project 1 _ Spam Message Classification/005 Apply Support vector Machine (SVM).mp433.8 MB
04 - Project 1 _ Spam Message Classification/005 Apply Support vector Machine (SVM)_en.vtt4.9 KB
04 - Project 1 _ Spam Message Classification/006 Predict Testing Data both model.mp416.2 MB
04 - Project 1 _ Spam Message Classification/006 Predict Testing Data both model_en.vtt3.7 KB
04 - Project 1 _ Spam Message Classification/25152746-spam.tsv501.8 KB
04 - Project 1 _ Spam Message Classification/external-assets-links.txt134 bytes
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/001 Business Problem.mp425.7 MB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/001 Business Problem_en.vtt4.5 KB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/002 Cleaning Text Data with NLTK - 1.mp449.6 MB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/002 Cleaning Text Data with NLTK - 1_en.vtt9.0 KB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/003 Cleaning Text Data with NLTK - 2.mp451.3 MB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/003 Cleaning Text Data with NLTK - 2_en.vtt6.9 KB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/004 Bag of Word Model.mp470.0 MB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/004 Bag of Word Model_en.vtt10.4 KB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/005 Apply Naive Bayes Algorithm.mp428.8 MB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/005 Apply Naive Bayes Algorithm_en.vtt4.6 KB
05 - Project 2 _ Restaurant Review Prediction (Good or bad)/25152756-Restaurant-Reviews.tsv59.9 KB
06 - Project 3 _ IMDB, Amazon and Yelp review Classification/001 Review Classification Part -1.mp479.4 MB
06 - Project 3 _ IMDB, Amazon and Yelp review Classification/001 Review Classification Part -1_en.vtt10.9 KB
06 - Project 3 _ IMDB, Amazon and Yelp review Classification/002 Review Classification Part - 2.mp472.4 MB
06 - Project 3 _ IMDB, Amazon and Yelp review Classification/002 Review Classification Part - 2_en.vtt9.2 KB
06 - Project 3 _ IMDB, Amazon and Yelp review Classification/25152800-amazon-cells-labelled.txt56.9 KB
06 - Project 3 _ IMDB, Amazon and Yelp review Classification/25152804-imdb-labelled.txt83.3 KB
06 - Project 3 _ IMDB, Amazon and Yelp review Classification/25152808-yelp-labelled.txt59.9 KB
07 - Project 4 _ Automated Text Summarization/001 Importing the libraries and Dataset.mp461.1 MB
07 - Project 4 _ Automated Text Summarization/001 Importing the libraries and Dataset_en.vtt7.7 KB
07 - Project 4 _ Automated Text Summarization/002 Create Word Frequency Counter.mp442.4 MB
07 - Project 4 _ Automated Text Summarization/002 Create Word Frequency Counter_en.vtt7.4 KB
07 - Project 4 _ Automated Text Summarization/003 Calculate Sentence Score.mp457.3 MB
07 - Project 4 _ Automated Text Summarization/003 Calculate Sentence Score_en.vtt6.6 KB
07 - Project 4 _ Automated Text Summarization/004 Extract summary of document.mp427.2 MB
07 - Project 4 _ Automated Text Summarization/004 Extract summary of document_en.vtt3.7 KB
08 - Project 5 _ Twitter sentiment Analysis/001 Setting up Twitter Developer application.mp449.3 MB
08 - Project 5 _ Twitter sentiment Analysis/001 Setting up Twitter Developer application_en.vtt7.6 KB
08 - Project 5 _ Twitter sentiment Analysis/002 Fetch Tweet from Tweeter server.mp431.0 MB
08 - Project 5 _ Twitter sentiment Analysis/002 Fetch Tweet from Tweeter server_en.vtt4.0 KB
08 - Project 5 _ Twitter sentiment Analysis/003 Find Setiment from Tweets.mp474.2 MB
08 - Project 5 _ Twitter sentiment Analysis/003 Find Setiment from Tweets_en.vtt10.2 KB
09 - Deep Learning Basics/001 The Neuron.mp4102.0 MB
09 - Deep Learning Basics/001 The Neuron_en.vtt5.9 KB
09 - Deep Learning Basics/002 Activation Function.mp4156.7 MB
09 - Deep Learning Basics/002 Activation Function_en.vtt8.4 KB
09 - Deep Learning Basics/003 Cost Function.mp451.8 MB
09 - Deep Learning Basics/003 Cost Function_en.vtt2.7 KB
09 - Deep Learning Basics/004 Gradient Descent and Back-Propagation.mp474.8 MB
09 - Deep Learning Basics/004 Gradient Descent and Back-Propagation_en.vtt3.9 KB
10 - Word Embeddings/001 Introduction to Word Embedding.mp4146.4 MB
10 - Word Embeddings/001 Introduction to Word Embedding_en.vtt11.7 KB
10 - Word Embeddings/002 Train Model for Embedding - I.mp471.4 MB
10 - Word Embeddings/002 Train Model for Embedding - I_en.vtt9.3 KB
10 - Word Embeddings/003 Train Model for Embedding - II.mp450.5 MB
10 - Word Embeddings/003 Train Model for Embedding - II_en.vtt6.5 KB
10 - Word Embeddings/004 Embeddings with Pretrained model.mp463.7 MB
10 - Word Embeddings/004 Embeddings with Pretrained model_en.vtt6.9 KB
10 - Word Embeddings/[Tutorialsplanet.NET].url128 bytes
11 - Project 6 _ Text Classification with CNN/001 Convolutional Neural Network Part 1.mp496.3 MB
11 - Project 6 _ Text Classification with CNN/001 Convolutional Neural Network Part 1_en.vtt4.9 KB
11 - Project 6 _ Text Classification with CNN/002 Convolutional Neural Network Part 2.mp481.1 MB
11 - Project 6 _ Text Classification with CNN/002 Convolutional Neural Network Part 2_en.vtt4.4 KB
11 - Project 6 _ Text Classification with CNN/003 Spam Detection with CNN - I.mp491.4 MB
11 - Project 6 _ Text Classification with CNN/003 Spam Detection with CNN - I_en.vtt10.4 KB
11 - Project 6 _ Text Classification with CNN/004 Spam Detection with CNN - II.mp478.0 MB
11 - Project 6 _ Text Classification with CNN/004 Spam Detection with CNN - II_en.vtt9.5 KB
11 - Project 6 _ Text Classification with CNN/25153370-spam.csv491.9 KB
12 - Project 7 _ Text Classification with RNN/001 Introduction to Recurrent Neural Networks.mp439.6 MB
12 - Project 7 _ Text Classification with RNN/001 Introduction to Recurrent Neural Networks_en.vtt2.1 KB
12 - Project 7 _ Text Classification with RNN/002 Vanishing Gradient Problem.mp438.9 MB
12 - Project 7 _ Text Classification with RNN/002 Vanishing Gradient Problem_en.vtt2.1 KB
12 - Project 7 _ Text Classification with RNN/003 LSTM and GRU.mp459.9 MB
12 - Project 7 _ Text Classification with RNN/003 LSTM and GRU_en.vtt3.7 KB
12 - Project 7 _ Text Classification with RNN/004 Spam Detection with RNN.mp464.4 MB
12 - Project 7 _ Text Classification with RNN/004 Spam Detection with RNN_en.vtt6.7 KB
12 - Project 7 _ Text Classification with RNN/25153382-spam.csv491.9 KB
13 - Project 8 _ Automatic Text Generation using TensorFlow, Keras and LSTM/001 Text Generation Part I.mp4114.3 MB
13 - Project 8 _ Automatic Text Generation using TensorFlow, Keras and LSTM/001 Text Generation Part I_en.vtt12.6 KB
13 - Project 8 _ Automatic Text Generation using TensorFlow, Keras and LSTM/002 Text Generation Part II.mp447.2 MB
13 - Project 8 _ Automatic Text Generation using TensorFlow, Keras and LSTM/002 Text Generation Part II_en.vtt6.3 KB
14 - FastText Library for Text Classification/001 fasttext Installation steps [Video].mp48.1 MB
14 - FastText Library for Text Classification/001 fasttext Installation steps [Video]_en.vtt2.1 KB
14 - FastText Library for Text Classification/002 fasttext Installation steps [Text].html466 bytes
14 - FastText Library for Text Classification/003 Virtual Box Installation.mp432.2 MB
14 - FastText Library for Text Classification/003 Virtual Box Installation_en.vtt5.9 KB
14 - FastText Library for Text Classification/004 Create Linux Virtual Machine.mp446.4 MB
14 - FastText Library for Text Classification/004 Create Linux Virtual Machine_en.vtt8.7 KB
14 - FastText Library for Text Classification/005 Install fasttext library.mp443.1 MB
14 - FastText Library for Text Classification/005 Install fasttext library_en.vtt5.8 KB
14 - FastText Library for Text Classification/006 Text Classification with Fasttext.mp4106.4 MB
14 - FastText Library for Text Classification/006 Text Classification with Fasttext_en.vtt15.7 KB
14 - FastText Library for Text Classification/27130276-reviews.txt70.1 KB
15 - Data analysis with Numpy/001 Introduction to NumPy.mp416.3 MB
15 - Data analysis with Numpy/001 Introduction to NumPy_en.vtt949 bytes
15 - Data analysis with Numpy/002 Numpy Arrays Part 1.mp416.8 MB
15 - Data analysis with Numpy/002 Numpy Arrays Part 1_en.vtt3.2 KB
15 - Data analysis with Numpy/003 Numpy Arrays Part 2.mp454.0 MB
15 - Data analysis with Numpy/003 Numpy Arrays Part 2_en.vtt8.9 KB
15 - Data analysis with Numpy/004 Numpy Arrays Part 3.mp427.3 MB
15 - Data analysis with Numpy/004 Numpy Arrays Part 3_en.vtt4.2 KB
15 - Data analysis with Numpy/005 Numpy Indexing and Selection Part 1.mp445.1 MB
15 - Data analysis with Numpy/005 Numpy Indexing and Selection Part 1_en.vtt6.8 KB
15 - Data analysis with Numpy/006 Numpy Indexing and Selection Part 2.mp426.6 MB
15 - Data analysis with Numpy/006 Numpy Indexing and Selection Part 2_en.vtt4.2 KB
15 - Data analysis with Numpy/007 Numpy Operations.mp429.2 MB
15 - Data analysis with Numpy/007 Numpy Operations_en.vtt3.4 KB
16 - Data analysis with Pandas/001 Pandas Introduction.mp412.5 MB
16 - Data analysis with Pandas/001 Pandas Introduction_en.vtt707 bytes
16 - Data analysis with Pandas/002 Pandas Series.mp470.0 MB
16 - Data analysis with Pandas/002 Pandas Series_en.vtt10.0 KB
16 - Data analysis with Pandas/003 DataFrames Part 1.mp478.0 MB
16 - Data analysis with Pandas/003 DataFrames Part 1_en.vtt11.1 KB
16 - Data analysis with Pandas/004 DataFrames Part 2.mp455.3 MB
16 - Data analysis with Pandas/004 DataFrames Part 2_en.vtt9.5 KB
16 - Data analysis with Pandas/005 DataFrames Part 3.mp456.4 MB
16 - Data analysis with Pandas/005 DataFrames Part 3_en.vtt8.8 KB
16 - Data analysis with Pandas/006 Missing Data.mp435.3 MB
16 - Data analysis with Pandas/006 Missing Data_en.vtt6.3 KB
16 - Data analysis with Pandas/007 Groupby Method.mp449.1 MB
16 - Data analysis with Pandas/007 Groupby Method_en.vtt7.1 KB
16 - Data analysis with Pandas/008 Merging, Joining and Concatenating DataFrames.mp457.2 MB
16 - Data analysis with Pandas/008 Merging, Joining and Concatenating DataFrames_en.vtt7.6 KB
16 - Data analysis with Pandas/009 Pandas Operations.mp438.8 MB
16 - Data analysis with Pandas/009 Pandas Operations_en.vtt7.3 KB
16 - Data analysis with Pandas/010 Reading and Writing Files in Pandas.mp446.5 MB
16 - Data analysis with Pandas/010 Reading and Writing Files in Pandas_en.vtt7.1 KB
17 - Data Visualization with Matplotlib/001 Matplotlib Part 1 - Functional Method.mp490.6 MB
17 - Data Visualization with Matplotlib/001 Matplotlib Part 1 - Functional Method_en.vtt9.9 KB
17 - Data Visualization with Matplotlib/002 Matplotlib Part 1 - Object Oriented Method.mp444.0 MB
17 - Data Visualization with Matplotlib/002 Matplotlib Part 1 - Object Oriented Method_en.vtt5.9 KB
17 - Data Visualization with Matplotlib/003 Matplotlib Part 2 - Subplots Method.mp437.8 MB
17 - Data Visualization with Matplotlib/003 Matplotlib Part 2 - Subplots Method_en.vtt4.9 KB
17 - Data Visualization with Matplotlib/004 Matplotlib Part 2 - Figure size, Aspect ratio and DPI.mp453.9 MB
17 - Data Visualization with Matplotlib/004 Matplotlib Part 2 - Figure size, Aspect ratio and DPI_en.vtt6.7 KB
17 - Data Visualization with Matplotlib/005 Matplotlib Part 3.mp450.1 MB
17 - Data Visualization with Matplotlib/005 Matplotlib Part 3_en.vtt4.8 KB
17 - Data Visualization with Matplotlib/006 Matplotlib Part 4.mp491.2 MB
17 - Data Visualization with Matplotlib/006 Matplotlib Part 4_en.vtt8.6 KB
18 - Appendix/001 Text File Processing - I.mp439.7 MB
18 - Appendix/001 Text File Processing - I_en.vtt7.8 KB
18 - Appendix/002 Text File Processing - II.mp458.0 MB
18 - Appendix/002 Text File Processing - II_en.vtt8.2 KB
18 - Appendix/003 Text File Processing - III.mp454.8 MB
18 - Appendix/003 Text File Processing - III_en.vtt11.1 KB
18 - Appendix/004 Text File Processing - IV.mp415.5 MB
18 - Appendix/004 Text File Processing - IV_en.vtt3.4 KB
18 - Appendix/005 Working with PDF File - I.mp445.6 MB
18 - Appendix/005 Working with PDF File - I_en.vtt8.3 KB
18 - Appendix/25154140-sample.pdf3.0 KB
[Tutorialsplanet.NET].url128 bytes
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