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585б |
| 0 |
26б |
| 001 [Slides] - Basic Text Processing.en.srt |
10.47Кб |
| 001 [Slides] - Basic Text Processing.mp4 |
91.54Мб |
| 001 [Slides] - NLTK Intro and Tokenizers.en.srt |
8.21Кб |
| 001 [Slides] - NLTK Intro and Tokenizers.mp4 |
77.37Мб |
| 001 [Slides] - Python Data Types and Libraries.en.srt |
11.54Кб |
| 001 [Slides] - Python Data Types and Libraries.mp4 |
90.28Мб |
| 001 [Slides] - Setting up the Environment.en.srt |
17.55Кб |
| 001 [Slides] - Setting up the Environment.mp4 |
124.25Мб |
| 001 Binary Vectorizer.en.srt |
24.87Кб |
| 001 Binary Vectorizer.mp4 |
134.48Мб |
| 001 Continuous Bag of Words Model (CBOW) Introduction.en.srt |
12.81Кб |
| 001 Continuous Bag of Words Model (CBOW) Introduction.mp4 |
69.80Мб |
| 001 Introduction.en.srt |
10.53Кб |
| 001 Introduction.mp4 |
108.71Мб |
| 001 Introduction to Word Vectors.en.srt |
3.31Кб |
| 001 Introduction to Word Vectors.mp4 |
9.61Мб |
| 001 Intro to Text Classification.en.srt |
5.03Кб |
| 001 Intro to Text Classification.mp4 |
14.40Мб |
| 001 Read Data from a CSV File - Using Pandas.en.srt |
13.89Кб |
| 001 Read Data from a CSV File - Using Pandas.mp4 |
69.19Мб |
| 001 Thank you!.en.srt |
1.29Кб |
| 001 Thank you!.mp4 |
13.80Мб |
| 002 [Slides] - Objects and Control Flow.en.srt |
13.37Кб |
| 002 [Slides] - Objects and Control Flow.mp4 |
102.77Мб |
| 002 [Slides] - Text Normalization Techniques.en.srt |
5.61Кб |
| 002 [Slides] - Text Normalization Techniques.mp4 |
49.69Мб |
| 002 Binary Word Vectors.en.srt |
10.42Кб |
| 002 Binary Word Vectors.mp4 |
56.56Мб |
| 002 CBOW - Creating Vocab and Binary Word Arrays.en.srt |
10.53Кб |
| 002 CBOW - Creating Vocab and Binary Word Arrays.mp4 |
56.57Мб |
| 002 Count Vectorizer.en.srt |
5.87Кб |
| 002 Count Vectorizer.mp4 |
32.40Мб |
| 002 Course Materials and Speed Up.html |
1.28Кб |
| 002 Installing the Anaconda Distribution.en.srt |
13.51Кб |
| 002 Installing the Anaconda Distribution.mp4 |
71.48Мб |
| 002 Loading Positive and Negative Movie Reviews.en.srt |
10.68Кб |
| 002 Loading Positive and Negative Movie Reviews.mp4 |
63.82Мб |
| 002 Manipulating Text Objects.en.srt |
16.30Кб |
| 002 Manipulating Text Objects.mp4 |
59.22Мб |
| 002 Read Data from a CSV File - Using Python CSV.en.srt |
6.74Кб |
| 002 Read Data from a CSV File - Using Python CSV.mp4 |
38.01Мб |
| 003 [Slides] - Functions, Pandas and Numpy.en.srt |
5.70Кб |
| 003 [Slides] - Functions, Pandas and Numpy.mp4 |
42.58Мб |
| 003 [Slides] - Part-of-Speech Tag and N-Grams.en.srt |
19.41Кб |
| 003 [Slides] - Part-of-Speech Tag and N-Grams.mp4 |
156.87Мб |
| 003 3 Alternatives to Setup your Environment.en.srt |
3.27Кб |
| 003 3 Alternatives to Setup your Environment.mp4 |
14.83Мб |
| 003 CBOW - Building Features and Target Variable.en.srt |
14.02Кб |
| 003 CBOW - Building Features and Target Variable.mp4 |
87.75Мб |
| 003 Combining Strings.en.srt |
5.53Кб |
| 003 Combining Strings.mp4 |
19.57Мб |
| 003 Pre-Processing Text for Text Classification.en.srt |
9.69Кб |
| 003 Pre-Processing Text for Text Classification.mp4 |
61.84Мб |
| 003 Read Data from a TXT File.en.srt |
8.31Кб |
| 003 Read Data from a TXT File.mp4 |
46.73Мб |
| 003 TF-IDF.en.srt |
14.36Кб |
| 003 TF-IDF.mp4 |
79.11Мб |
| 003 Word Co-Occurence Matrices.en.srt |
11.54Кб |
| 003 Word Co-Occurence Matrices.mp4 |
71.65Мб |
| 004 [1] - Creating an Environment and Installing Libraries via Anaconda.en.srt |
7.16Кб |
| 004 [1] - Creating an Environment and Installing Libraries via Anaconda.mp4 |
26.01Мб |
| 004 CBOW - Accuracy of Random Model and Training Process.en.srt |
21.01Кб |
| 004 CBOW - Accuracy of Random Model and Training Process.mp4 |
105.71Мб |
| 004 Filling Co-Occurence Matrix.en.srt |
13.43Кб |
| 004 Filling Co-Occurence Matrix.mp4 |
101.81Мб |
| 004 Iterating Strings and Format Method.en.srt |
8.37Кб |
| 004 Iterating Strings and Format Method.mp4 |
39.17Мб |
| 004 Jupyter Notebook Overview.en.srt |
8.77Кб |
| 004 Jupyter Notebook Overview.mp4 |
34.30Мб |
| 004 Log Ratio Intuition and Word Influence.en.srt |
24.52Кб |
| 004 Log Ratio Intuition and Word Influence.mp4 |
130.01Мб |
| 004 Natural Language Toolkit Introduction and Sentence Tokenizer.en.srt |
13.89Кб |
| 004 Natural Language Toolkit Introduction and Sentence Tokenizer.mp4 |
91.42Мб |
| 004 Scraping a Web Page using Requests and BeautifulSoup - Wikipedia Example.en.srt |
18.74Кб |
| 004 Scraping a Web Page using Requests and BeautifulSoup - Wikipedia Example.mp4 |
153.67Мб |
| 004 Text Representation - Exercises.en.srt |
1.28Кб |
| 004 Text Representation - Exercises.mp4 |
7.67Мб |
| 005 [2] - Creating an Environment by Importing the YML File.en.srt |
3.90Кб |
| 005 [2] - Creating an Environment by Importing the YML File.mp4 |
14.20Мб |
| 005 CBOW - Training the Neural Network.en.srt |
19.76Кб |
| 005 CBOW - Training the Neural Network.mp4 |
108.99Мб |
| 005 Python Integers, Floats and Strings.en.srt |
10.64Кб |
| 005 Python Integers, Floats and Strings.mp4 |
41.50Мб |
| 005 Scraping a Web Page using Requests and BeautifulSoup - Yahoo Finance Example.en.srt |
22.42Кб |
| 005 Scraping a Web Page using Requests and BeautifulSoup - Yahoo Finance Example.mp4 |
162.84Мб |
| 005 Stemming and Vectorizing the Reviews.en.srt |
18.70Кб |
| 005 Stemming and Vectorizing the Reviews.mp4 |
106.69Мб |
| 005 Testing if String is in Sentence.en.srt |
3.58Кб |
| 005 Testing if String is in Sentence.mp4 |
13.56Мб |
| 005 Visualizing Word Vectors.en.srt |
11.08Кб |
| 005 Visualizing Word Vectors.mp4 |
65.66Мб |
| 005 Word Tokenizer.en.srt |
12.58Кб |
| 005 Word Tokenizer.mp4 |
52.99Мб |
| 006 CBOW - Obtaining Word Vectors (Embeddings).en.srt |
9.77Кб |
| 006 CBOW - Obtaining Word Vectors (Embeddings).mp4 |
56.18Мб |
| 006 Escaping Characters.en.srt |
9.78Кб |
| 006 Escaping Characters.mp4 |
36.04Мб |
| 006 Launching a Jupyter Notebook via Anaconda Navigator.en.srt |
6.70Кб |
| 006 Launching a Jupyter Notebook via Anaconda Navigator.mp4 |
27.74Мб |
| 006 Logistic Regression Intuition and Training Process.en.srt |
9.81Кб |
| 006 Logistic Regression Intuition and Training Process.mp4 |
39.41Мб |
| 006 Python Libraries.en.srt |
5.88Кб |
| 006 Python Libraries.mp4 |
27.30Мб |
| 006 Scraping a Web Page - Errors in Request.en.srt |
5.13Кб |
| 006 Scraping a Web Page - Errors in Request.mp4 |
32.47Мб |
| 006 Similarity between Words - Cosine.en.srt |
15.09Кб |
| 006 Similarity between Words - Cosine.mp4 |
70.88Мб |
| 006 Tokenizer Application and Cleaning Tokens.en.srt |
14.42Кб |
| 006 Tokenizer Application and Cleaning Tokens.mp4 |
60.15Мб |
| 007 [3] - Creating an Environment via Conda.en.srt |
6.03Кб |
| 007 [3] - Creating an Environment via Conda.mp4 |
39.37Мб |
| 007 Counting Frequency of Digits in Sentence.en.srt |
20.36Кб |
| 007 Counting Frequency of Digits in Sentence.mp4 |
105.33Мб |
| 007 Pre-Processing Wikipedia Data for CBOW Model.en.srt |
11.56Кб |
| 007 Pre-Processing Wikipedia Data for CBOW Model.mp4 |
52.97Мб |
| 007 Python Lists and Sets.en.srt |
7.31Кб |
| 007 Python Lists and Sets.mp4 |
30.23Мб |
| 007 Scraping a Web Page using Specific Libraries.en.srt |
4.81Кб |
| 007 Scraping a Web Page using Specific Libraries.mp4 |
36.62Мб |
| 007 Sentence Length, Conversions and Casing Methods.en.srt |
7.93Кб |
| 007 Sentence Length, Conversions and Casing Methods.mp4 |
29.67Мб |
| 007 Sigmoid Function and One Feature Prediction.en.srt |
10.33Кб |
| 007 Sigmoid Function and One Feature Prediction.mp4 |
65.49Мб |
| 007 Word Similarities from Co-Occurence Matrix.en.srt |
10.16Кб |
| 007 Word Similarities from Co-Occurence Matrix.mp4 |
57.46Мб |
| 008 Building Features and Target for Wikipedia Data.en.srt |
16.24Кб |
| 008 Building Features and Target for Wikipedia Data.mp4 |
92.24Мб |
| 008 FreqDist NLTK Function.en.srt |
8.73Кб |
| 008 FreqDist NLTK Function.mp4 |
41.49Мб |
| 008 Gradient Descent Intuition by Adjusting Weights.en.srt |
13.62Кб |
| 008 Gradient Descent Intuition by Adjusting Weights.mp4 |
76.67Мб |
| 008 Installing Libraries via Conda.en.srt |
3.93Кб |
| 008 Installing Libraries via Conda.mp4 |
15.02Мб |
| 008 Is Alpha, Strip and Split.en.srt |
7.85Кб |
| 008 Is Alpha, Strip and Split.mp4 |
31.34Мб |
| 008 Python Dictionaries and Tuples.en.srt |
5.39Кб |
| 008 Python Dictionaries and Tuples.mp4 |
22.52Мб |
| 008 Reading Text Data - Exercises.en.srt |
1.93Кб |
| 008 Reading Text Data - Exercises.mp4 |
10.03Мб |
| 008 Word Vectors - Exercises.en.srt |
968б |
| 008 Word Vectors - Exercises.mp4 |
6.67Мб |
| 009 Fitting Neural Network on Wikipedia Data.en.srt |
11.39Кб |
| 009 Fitting Neural Network on Wikipedia Data.mp4 |
42.77Мб |
| 009 Join and Capitalize.en.srt |
4.01Кб |
| 009 Join and Capitalize.mp4 |
16.00Мб |
| 009 Launching a Jupyter Notebook via Conda.en.srt |
4.04Кб |
| 009 Launching a Jupyter Notebook via Conda.mp4 |
22.08Мб |
| 009 Porter, Snowball and Lancaster Stemmers.en.srt |
17.89Кб |
| 009 Porter, Snowball and Lancaster Stemmers.mp4 |
99.22Мб |
| 009 Python Control Flow.en.srt |
17.14Кб |
| 009 Python Control Flow.mp4 |
71.94Мб |
| 009 Train and Test Split.en.srt |
6.31Кб |
| 009 Train and Test Split.mp4 |
27.73Мб |
| 010 Fitting and Evaluating Model.en.srt |
6.35Кб |
| 010 Fitting and Evaluating Model.mp4 |
32.52Мб |
| 010 Performance of the Neural Network.en.srt |
8.77Кб |
| 010 Performance of the Neural Network.mp4 |
50.36Мб |
| 010 Python Functions.en.srt |
9.97Кб |
| 010 Python Functions.mp4 |
40.17Мб |
| 010 Replace, Count and Find.en.srt |
8.46Кб |
| 010 Replace, Count and Find.mp4 |
35.41Мб |
| 010 Stemming Sentences.en.srt |
11.83Кб |
| 010 Stemming Sentences.mp4 |
70.04Мб |
| 010 Testing if your environment is OK.en.srt |
10.99Кб |
| 010 Testing if your environment is OK.mp4 |
38.11Мб |
| 011 Model Regularization.en.srt |
4.06Кб |
| 011 Model Regularization.mp4 |
23.93Мб |
| 011 Numpy Overview.en.srt |
9.51Кб |
| 011 Numpy Overview.mp4 |
34.99Мб |
| 011 Predicting a Word Given a Context.en.srt |
9.61Кб |
| 011 Predicting a Word Given a Context.mp4 |
52.07Мб |
| 011 Summary on Environment Setup.en.srt |
4.73Кб |
| 011 Summary on Environment Setup.mp4 |
14.01Мб |
| 011 WordNet Lemmatizer.en.srt |
12.54Кб |
| 011 WordNet Lemmatizer.mp4 |
55.42Мб |
| 011 Working with Text - Exercises.en.srt |
1.12Кб |
| 011 Working with Text - Exercises.mp4 |
7.34Мб |
| 012 Obtaining the Weights_Coefficients of Regression.en.srt |
6.72Кб |
| 012 Obtaining the Weights_Coefficients of Regression.mp4 |
29.20Мб |
| 012 Pandas Overview.en.srt |
8.57Кб |
| 012 Pandas Overview.mp4 |
32.71Мб |
| 012 Part-of-Speech (POS) Tagging.en.srt |
16.54Кб |
| 012 Part-of-Speech (POS) Tagging.mp4 |
83.59Мб |
| 012 Retrieving Word Embeddings and Word Similarities.en.srt |
18.64Кб |
| 012 Retrieving Word Embeddings and Word Similarities.mp4 |
104.70Мб |
| 013 Predicting New Sentences Sentiment.en.srt |
15.11Кб |
| 013 Predicting New Sentences Sentiment.mp4 |
93.93Мб |
| 013 Training a POS Tagger from Scratch - Accessing Tagged Data from Brown Corpus.en.srt |
12.98Кб |
| 013 Training a POS Tagger from Scratch - Accessing Tagged Data from Brown Corpus.mp4 |
68.33Мб |
| 013 Tutorial - How to Complete the Exercises.en.srt |
7.16Кб |
| 013 Tutorial - How to Complete the Exercises.mp4 |
39.38Мб |
| 013 Word2Vec.en.srt |
20.03Кб |
| 013 Word2Vec.mp4 |
92.70Мб |
| 014 Python Quick Course - Exercises.en.srt |
2.56Кб |
| 014 Python Quick Course - Exercises.mp4 |
11.16Мб |
| 014 Training a POS Tagger from Scratch - Unigram Tagger.en.srt |
16.47Кб |
| 014 Training a POS Tagger from Scratch - Unigram Tagger.mp4 |
80.23Мб |
| 014 Word2Vec - Operations with Vectors.en.srt |
12.39Кб |
| 014 Word2Vec - Operations with Vectors.mp4 |
73.27Мб |
| 015 Training a POS Tagger from Scratch - Bigram Tagger.en.srt |
17.12Кб |
| 015 Training a POS Tagger from Scratch - Bigram Tagger.mp4 |
90.50Мб |
| 015 Word2Vec - Word Clustering.en.srt |
17.73Кб |
| 015 Word2Vec - Word Clustering.mp4 |
84.24Мб |
| 016 Continuous Bag of Words Implementation - Exercises.en.srt |
2.04Кб |
| 016 Continuous Bag of Words Implementation - Exercises.mp4 |
9.55Мб |
| 016 Plotting the Frequency of Tags in a Sentence.en.srt |
9.88Кб |
| 016 Plotting the Frequency of Tags in a Sentence.mp4 |
59.88Мб |
| 017 Lemmatization and POS Tagging.en.srt |
16.90Кб |
| 017 Lemmatization and POS Tagging.mp4 |
100.40Мб |
| 018 Stop Words.en.srt |
24.51Кб |
| 018 Stop Words.mp4 |
115.82Мб |
| 019 N-Grams.en.srt |
10.70Кб |
| 019 N-Grams.mp4 |
54.13Мб |
| 020 Natural Language Toolkit - Exercises.en.srt |
1.36Кб |
| 020 Natural Language Toolkit - Exercises.mp4 |
6.98Мб |
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