Udemy - Machine Learning Natural Language Processing in Python (V2) (12.2024)

Creation Time	July 7, 2025, 12:04 p.m.
Last Access Time	July 7, 2025, 12:37 p.m.
File Size	6.8 GB
Keywords	2024 12 Natural Language Python Processing - Udemy Machine V2 Learning in
Total Requests	6
Total Files	483
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18 - Recurrent Neural Networks/9 -Parts-of-Speech (POS) Tagging in Tensorflow.mp4 145.1 MB
3 - Vector Models and Text Preprocessing/14 -TF-IDF (Code).mp4 124.9 MB
16 - Feedforward Artificial Neural Networks/13 -CBOW in Tensorflow (Advanced).mp4 117.6 MB
22 - Effective Learning Strategies for Machine Learning FAQ/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 108.1 MB
9 - Spam Detection/6 -Spam Detection in Python.mp4 107.6 MB
7 - Cipher Decryption (Advanced)/4 -Genetic Algorithms.mp4 105.2 MB
3 - Vector Models and Text Preprocessing/10 -Count Vectorizer (Code).mp4 102.0 MB
6 - Article Spinner (Intermediate)/4 -Article Spinner in Python (pt 1).mp4 95.9 MB
16 - Feedforward Artificial Neural Networks/4 -Activation Functions.mp4 89.3 MB
17 - Convolutional Neural Networks/6 -CNN Architecture.mp4 89.3 MB
11 - Text Summarization/8 -TextRank in Python (Advanced).mp4 82.3 MB
18 - Recurrent Neural Networks/6 -GRU and LSTM (pt 1).mp4 82.2 MB
13 - Latent Semantic Analysis (Latent Semantic Indexing)/2 -SVD (Singular Value Decomposition) Intuition.mp4 81.8 MB
15 - The Neuron/4 -Text Classification in Tensorflow.mp4 81.7 MB
17 - Convolutional Neural Networks/2 -What is Convolution.mp4 79.9 MB
3 - Vector Models and Text Preprocessing/16 -How to Build TF-IDF From Scratch.mp4 79.8 MB
22 - Effective Learning Strategies for Machine Learning FAQ/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 79.7 MB
11 - Text Summarization/4 -Text Summarization in Python.mp4 78.2 MB
6 - Article Spinner (Intermediate)/5 -Article Spinner in Python (pt 2).mp4 75.4 MB
17 - Convolutional Neural Networks/5 -Convolution on Color Images.mp4 75.2 MB
3 - Vector Models and Text Preprocessing/9 -Stemming and Lemmatization Demo.mp4 74.8 MB
3 - Vector Models and Text Preprocessing/6 -Tokenization.mp4 73.5 MB
1 - Introduction/1 -Introduction and Outline.mp4 73.0 MB
12 - Topic Modeling/6 -Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4 72.4 MB
5 - Markov Models (Intermediate)/8 -Building a Text Classifier (Code pt 2).mp4 72.2 MB
21 - Extra Help With Python Coding for Beginners FAQ/1 -How to Code by Yourself (part 1).mp4 71.9 MB
21 - Extra Help With Python Coding for Beginners FAQ/3 -Proof that using Jupyter Notebook is the same as not using it.mp4 69.4 MB
15 - The Neuron/2 -Fitting a Line.mp4 68.6 MB
3 - Vector Models and Text Preprocessing/18 -Neural Word Embeddings Demo.mp4 66.8 MB
7 - Cipher Decryption (Advanced)/3 -Language Models (Review).mp4 65.5 MB
21 - Extra Help With Python Coding for Beginners FAQ/6 -How to use Github & Extra Coding Tips (Optional).mp4 63.9 MB
10 - Sentiment Analysis/2 -Logistic Regression Intuition (pt 1).mp4 63.6 MB
10 - Sentiment Analysis/6 -Sentiment Analysis in Python (pt 1).mp4 63.1 MB
5 - Markov Models (Intermediate)/11 -Language Model (Code pt 1).mp4 62.8 MB
9 - Spam Detection/4 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 60.2 MB
12 - Topic Modeling/5 -Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4 60.2 MB
3 - Vector Models and Text Preprocessing/12 -TF-IDF (Theory).mp4 58.6 MB
3 - Vector Models and Text Preprocessing/8 -Stemming and Lemmatization.mp4 57.9 MB
5 - Markov Models (Intermediate)/7 -Building a Text Classifier (Code pt 1).mp4 57.7 MB
13 - Latent Semantic Analysis (Latent Semantic Indexing)/4 -Latent Semantic Analysis Latent Semantic Indexing in Python.mp4 57.6 MB
3 - Vector Models and Text Preprocessing/5 -Count Vectorizer (Theory).mp4 57.4 MB
18 - Recurrent Neural Networks/5 -RNNs Paying Attention to Shapes.mp4 57.2 MB
16 - Feedforward Artificial Neural Networks/3 -The Geometrical Picture.mp4 56.5 MB
3 - Vector Models and Text Preprocessing/21 -How To Do NLP In Other Languages.mp4 56.0 MB
12 - Topic Modeling/2 -Latent Dirichlet Allocation (LDA) - Essentials.mp4 55.2 MB
9 - Spam Detection/5 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 54.0 MB
20 - Setting Up Your Environment FAQ/2 -Anaconda Environment Setup.mp4 52.6 MB
12 - Topic Modeling/7 -Non-Negative Matrix Factorization (NMF) Intuition.mp4 52.5 MB
5 - Markov Models (Intermediate)/12 -Language Model (Code pt 2).mp4 52.4 MB
10 - Sentiment Analysis/7 -Sentiment Analysis in Python (pt 2).mp4 52.0 MB
15 - The Neuron/6 -How does a model learn.mp4 51.6 MB
9 - Spam Detection/2 -Naive Bayes Intuition.mp4 51.3 MB
20 - Setting Up Your Environment FAQ/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 50.9 MB
18 - Recurrent Neural Networks/7 -GRU and LSTM (pt 2).mp4 50.3 MB
16 - Feedforward Artificial Neural Networks/8 -Text Preprocessing Code Preparation.mp4 50.0 MB
11 - Text Summarization/6 -TextRank - How It Really Works (Advanced).mp4 49.3 MB
21 - Extra Help With Python Coding for Beginners FAQ/2 -How to Code by Yourself (part 2).mp4 49.2 MB
3 - Vector Models and Text Preprocessing/3 -What is a Vector.mp4 48.9 MB
3 - Vector Models and Text Preprocessing/15 -Word-to-Index Mapping.mp4 47.6 MB
16 - Feedforward Artificial Neural Networks/2 -Forward Propagation.mp4 46.7 MB
11 - Text Summarization/5 -TextRank Intuition.mp4 45.9 MB
18 - Recurrent Neural Networks/8 -RNN for Text Classification in Tensorflow.mp4 45.9 MB
5 - Markov Models (Intermediate)/3 -The Markov Model.mp4 45.8 MB
3 - Vector Models and Text Preprocessing/17 -Neural Word Embeddings.mp4 45.5 MB
15 - The Neuron/5 -The Neuron.mp4 45.3 MB
11 - Text Summarization/9 -Text Summarization in Python - The Easy Way (Beginner).mp4 45.2 MB
3 - Vector Models and Text Preprocessing/11 -Vector Similarity.mp4 45.1 MB
5 - Markov Models (Intermediate)/9 -Language Model (Theory).mp4 45.0 MB
16 - Feedforward Artificial Neural Networks/5 -Multiclass Classification.mp4 44.4 MB
21 - Extra Help With Python Coding for Beginners FAQ/4 -Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 43.6 MB
19 - Course Conclusion/2 -Where is BERT, ChatGPT, GPT-4,.mp4 42.8 MB
10 - Sentiment Analysis/1 -Sentiment Analysis - Problem Description.mp4 42.7 MB
16 - Feedforward Artificial Neural Networks/10 -Embeddings.mp4 42.3 MB
18 - Recurrent Neural Networks/4 -RNN Code Preparation.mp4 42.1 MB
17 - Convolutional Neural Networks/8 -Convolutional Neural Network for NLP in Tensorflow.mp4 42.0 MB
6 - Article Spinner (Intermediate)/1 -Article Spinning - Problem Description.mp4 41.9 MB
18 - Recurrent Neural Networks/3 -Simple RNN Elman Unit (pt 2).mp4 41.2 MB
7 - Cipher Decryption (Advanced)/10 -Code pt 5.mp4 41.0 MB
18 - Recurrent Neural Networks/2 -Simple RNN Elman Unit (pt 1).mp4 40.8 MB
17 - Convolutional Neural Networks/7 -CNNs for Text.mp4 40.5 MB
23 - Appendix FAQ Finale/2 -BONUS.mp4 40.4 MB
10 - Sentiment Analysis/4 -Logistic Regression Training and Interpretation (pt 3).mp4 39.6 MB
7 - Cipher Decryption (Advanced)/11 -Code pt 6.mp4 39.4 MB
7 - Cipher Decryption (Advanced)/7 -Code pt 2.mp4 39.1 MB
22 - Effective Learning Strategies for Machine Learning FAQ/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39.0 MB
16 - Feedforward Artificial Neural Networks/1 -ANN - Section Introduction.mp4 38.6 MB
16 - Feedforward Artificial Neural Networks/15 -Aside How to Choose Hyperparameters (Optional).mp4 38.1 MB
19 - Course Conclusion/1 -What to Learn Next.mp4 37.4 MB
16 - Feedforward Artificial Neural Networks/7 -Text Classification ANN in Tensorflow.mp4 36.1 MB
12 - Topic Modeling/8 -Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp4 36.0 MB
13 - Latent Semantic Analysis (Latent Semantic Indexing)/3 -LSA LSI Applying SVD to NLP.mp4 34.4 MB
5 - Markov Models (Intermediate)/4 -Probability Smoothing and Log-Probabilities.mp4 34.1 MB
15 - The Neuron/3 -Classification Code Preparation.mp4 32.9 MB
5 - Markov Models (Intermediate)/2 -The Markov Property.mp4 32.2 MB
18 - Recurrent Neural Networks/10 -Named Entity Recognition (NER) in Tensorflow.mp4 31.5 MB
9 - Spam Detection/1 -Spam Detection - Problem Description.mp4 31.3 MB
16 - Feedforward Artificial Neural Networks/9 -Text Preprocessing in Tensorflow.mp4 30.9 MB
17 - Convolutional Neural Networks/4 -What is Convolution (Weight Sharing).mp4 29.8 MB
8 - Machine Learning Models (Introduction)/1 -Machine Learning Models (Introduction).mp4 29.6 MB
7 - Cipher Decryption (Advanced)/8 -Code pt 3.mp4 29.5 MB
5 - Markov Models (Intermediate)/6 -Building a Text Classifier (Exercise Prompt).mp4 29.4 MB
13 - Latent Semantic Analysis (Latent Semantic Indexing)/5 -LSA LSI Exercises.mp4 29.0 MB
5 - Markov Models (Intermediate)/5 -Building a Text Classifier (Theory).mp4 28.9 MB
5 - Markov Models (Intermediate)/10 -Language Model (Exercise Prompt).mp4 28.8 MB
3 - Vector Models and Text Preprocessing/2 -Basic Definitions for NLP.mp4 28.4 MB
6 - Article Spinner (Intermediate)/6 -Case Study Article Spinning Gone Wrong.mp4 28.2 MB
3 - Vector Models and Text Preprocessing/22 -Suggestion Box.mp4 27.2 MB
4 - Probabilistic Models (Introduction)/1 -Probabilistic Models (Introduction).mp4 26.9 MB
1 - Introduction/2 -Are You Beginner, Intermediate, or Advanced All are OK!.mp4 26.7 MB
7 - Cipher Decryption (Advanced)/1 -Section Introduction.mp4 26.3 MB
11 - Text Summarization/2 -Text Summarization Using Vectors.mp4 25.8 MB
11 - Text Summarization/1 -Text Summarization Section Introduction.mp4 25.8 MB
7 - Cipher Decryption (Advanced)/9 -Code pt 4.mp4 25.6 MB
17 - Convolutional Neural Networks/1 -CNN - Section Introduction.mp4 25.6 MB
6 - Article Spinner (Intermediate)/3 -Article Spinner Exercise Prompt.mp4 24.6 MB
17 - Convolutional Neural Networks/3 -What is Convolution (Pattern Matching).mp4 24.6 MB
14 - Deep Learning (Introduction)/1 -Deep Learning Introduction (Intermediate-Advanced).mp4 24.5 MB
21 - Extra Help With Python Coding for Beginners FAQ/5 -Where To Get the Code Troubleshooting.mp4 24.3 MB
7 - Cipher Decryption (Advanced)/14 -Section Conclusion.mp4 24.2 MB
10 - Sentiment Analysis/3 -Multiclass Logistic Regression (pt 2).mp4 23.6 MB
3 - Vector Models and Text Preprocessing/7 -Stopwords.mp4 23.4 MB
20 - Setting Up Your Environment FAQ/1 -Pre-Installation Check.mp4 22.7 MB
2 - Getting Set Up/1 -Where To Get the Code.mp4 22.5 MB
2 - Getting Set Up/3 -Temporary 403 Errors.mp4 22.0 MB
13 - Latent Semantic Analysis (Latent Semantic Indexing)/1 -LSA LSI Section Introduction.mp4 20.9 MB
18 - Recurrent Neural Networks/1 -RNN - Section Introduction.mp4 20.9 MB
3 - Vector Models and Text Preprocessing/19 -Vector Models & Text Preprocessing Summary.mp4 20.9 MB
7 - Cipher Decryption (Advanced)/5 -Code Preparation.mp4 20.6 MB
16 - Feedforward Artificial Neural Networks/6 -ANN Code Preparation.mp4 20.1 MB
11 - Text Summarization/10 -Text Summarization Section Summary.mp4 20.1 MB
22 - Effective Learning Strategies for Machine Learning FAQ/1 -How to Succeed in this Course (Long Version).mp4 17.9 MB
7 - Cipher Decryption (Advanced)/13 -Real-World Application Acoustic Keylogger.mp4 17.7 MB
3 - Vector Models and Text Preprocessing/1 -Vector Models & Text Preprocessing Intro.mp4 17.5 MB
7 - Cipher Decryption (Advanced)/2 -Ciphers.mp4 17.2 MB
12 - Topic Modeling/1 -Topic Modeling Section Introduction.mp4 17.0 MB
10 - Sentiment Analysis/5 -Sentiment Analysis - Exercise Prompt.mp4 16.6 MB
23 - Appendix FAQ Finale/1 -What is the Appendix.mp4 16.4 MB
2 - Getting Set Up/2 -How to Succeed in This Course.mp4 16.3 MB
7 - Cipher Decryption (Advanced)/6 -Code pt 1.mp4 16.0 MB
6 - Article Spinner (Intermediate)/2 -Article Spinning - N-Gram Approach.mp4 15.9 MB
16 - Feedforward Artificial Neural Networks/11 -CBOW (Advanced).mp4 15.8 MB
5 - Markov Models (Intermediate)/13 -Markov Models Section Summary.mp4 15.6 MB
7 - Cipher Decryption (Advanced)/12 -Cipher Decryption - Additional Discussion.mp4 14.7 MB
18 - Recurrent Neural Networks/11 -Exercise Return to CNNs (Advanced).mp4 14.6 MB
12 - Topic Modeling/3 -LDA - Code Preparation.mp4 14.5 MB
3 - Vector Models and Text Preprocessing/4 -Bag of Words.mp4 13.9 MB
3 - Vector Models and Text Preprocessing/13 -(Interactive) Recommender Exercise Prompt.mp4 13.4 MB
5 - Markov Models (Intermediate)/1 -Markov Models Section Introduction.mp4 13.1 MB
15 - The Neuron/1 -The Neuron - Section Introduction.mp4 11.0 MB
15 - The Neuron/7 -The Neuron - Section Summary.mp4 10.3 MB
12 - Topic Modeling/9 -Topic Modeling Section Summary.mp4 9.8 MB
18 - Recurrent Neural Networks/12 -RNN - Section Summary.mp4 9.1 MB
12 - Topic Modeling/4 -LDA - Maybe Useful Picture (Optional).mp4 9.0 MB
9 - Spam Detection/3 -Spam Detection - Exercise Prompt.mp4 8.7 MB
17 - Convolutional Neural Networks/9 -CNN - Section Summary.mp4 8.2 MB
11 - Text Summarization/3 -Text Summarization Exercise Prompt.mp4 8.1 MB
16 - Feedforward Artificial Neural Networks/14 -ANN - Section Summary.mp4 7.6 MB
11 - Text Summarization/7 -TextRank Exercise Prompt (Advanced).mp4 7.5 MB
3 - Vector Models and Text Preprocessing/20 -Text Summarization Preview.mp4 6.3 MB
16 - Feedforward Artificial Neural Networks/12 -CBOW Exercise Prompt.mp4 5.0 MB
22 - Effective Learning Strategies for Machine Learning FAQ/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28.3 KB
22 - Effective Learning Strategies for Machine Learning FAQ/subtitles/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.ko_KR.vtt 27.5 KB
7 - Cipher Decryption (Advanced)/4 -Genetic Algorithms.vtt 25.4 KB
17 - Convolutional Neural Networks/6 -CNN Architecture.vtt 25.0 KB
7 - Cipher Decryption (Advanced)/subtitles/4 -Genetic Algorithms.ko_KR.vtt 24.7 KB
17 - Convolutional Neural Networks/subtitles/6 -CNN Architecture.ko_KR.vtt 24.5 KB
3 - Vector Models and Text Preprocessing/14 -TF-IDF (Code).vtt 21.6 KB
3 - Vector Models and Text Preprocessing/subtitles/14 -TF-IDF (Code).ko_KR.vtt 21.1 KB
22 - Effective Learning Strategies for Machine Learning FAQ/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).vtt 20.7 KB
22 - Effective Learning Strategies for Machine Learning FAQ/subtitles/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).ko_KR.vtt 20.5 KB
18 - Recurrent Neural Networks/6 -GRU and LSTM (pt 1).vtt 20.3 KB
16 - Feedforward Artificial Neural Networks/4 -Activation Functions.vtt 20.0 KB
18 - Recurrent Neural Networks/subtitles/9 -Parts-of-Speech (POS) Tagging in Tensorflow.ko_KR.vtt 19.9 KB
21 - Extra Help With Python Coding for Beginners FAQ/1 -How to Code by Yourself (part 1).vtt 19.8 KB
18 - Recurrent Neural Networks/9 -Parts-of-Speech (POS) Tagging in Tensorflow.vtt 19.8 KB
10 - Sentiment Analysis/2 -Logistic Regression Intuition (pt 1).vtt 19.7 KB
18 - Recurrent Neural Networks/subtitles/6 -GRU and LSTM (pt 1).ko_KR.vtt 19.5 KB
16 - Feedforward Artificial Neural Networks/subtitles/4 -Activation Functions.ko_KR.vtt 19.2 KB
10 - Sentiment Analysis/subtitles/2 -Logistic Regression Intuition (pt 1).ko_KR.vtt 18.9 KB
21 - Extra Help With Python Coding for Beginners FAQ/subtitles/1 -How to Code by Yourself (part 1).ko_KR.vtt 18.9 KB
17 - Convolutional Neural Networks/5 -Convolution on Color Images.vtt 18.3 KB
16 - Feedforward Artificial Neural Networks/subtitles/13 -CBOW in Tensorflow (Advanced).ko_KR.vtt 18.1 KB
20 - Setting Up Your Environment FAQ/subtitles/2 -Anaconda Environment Setup.ko_KR.vtt 18.1 KB
6 - Article Spinner (Intermediate)/4 -Article Spinner in Python (pt 1).vtt 18.1 KB
17 - Convolutional Neural Networks/2 -What is Convolution.vtt 18.0 KB
17 - Convolutional Neural Networks/subtitles/2 -What is Convolution.ko_KR.vtt 18.0 KB
7 - Cipher Decryption (Advanced)/3 -Language Models (Review).vtt 18.0 KB
6 - Article Spinner (Intermediate)/subtitles/4 -Article Spinner in Python (pt 1).ko_KR.vtt 18.0 KB
16 - Feedforward Artificial Neural Networks/13 -CBOW in Tensorflow (Advanced).vtt 17.7 KB
12 - Topic Modeling/5 -Latent Dirichlet Allocation (LDA) - Intuition (Advanced).vtt 17.6 KB
12 - Topic Modeling/subtitles/5 -Latent Dirichlet Allocation (LDA) - Intuition (Advanced).ko_KR.vtt 17.6 KB
3 - Vector Models and Text Preprocessing/subtitles/6 -Tokenization.ko_KR.vtt 17.6 KB
20 - Setting Up Your Environment FAQ/2 -Anaconda Environment Setup.vtt 17.4 KB
3 - Vector Models and Text Preprocessing/6 -Tokenization.vtt 17.3 KB
17 - Convolutional Neural Networks/subtitles/5 -Convolution on Color Images.ko_KR.vtt 17.3 KB
9 - Spam Detection/6 -Spam Detection in Python.vtt 16.8 KB
3 - Vector Models and Text Preprocessing/5 -Count Vectorizer (Theory).vtt 16.8 KB
3 - Vector Models and Text Preprocessing/10 -Count Vectorizer (Code).vtt 16.7 KB
3 - Vector Models and Text Preprocessing/subtitles/10 -Count Vectorizer (Code).ko_KR.vtt 16.6 KB
9 - Spam Detection/subtitles/6 -Spam Detection in Python.ko_KR.vtt 16.5 KB
7 - Cipher Decryption (Advanced)/subtitles/3 -Language Models (Review).ko_KR.vtt 16.4 KB
15 - The Neuron/subtitles/2 -Fitting a Line.ko_KR.vtt 16.3 KB
3 - Vector Models and Text Preprocessing/subtitles/16 -How to Build TF-IDF From Scratch.ko_KR.vtt 16.2 KB
3 - Vector Models and Text Preprocessing/16 -How to Build TF-IDF From Scratch.vtt 16.2 KB
3 - Vector Models and Text Preprocessing/subtitles/12 -TF-IDF (Theory).ko_KR.vtt 16.2 KB
15 - The Neuron/2 -Fitting a Line.vtt 16.1 KB
3 - Vector Models and Text Preprocessing/12 -TF-IDF (Theory).vtt 16.0 KB
3 - Vector Models and Text Preprocessing/subtitles/5 -Count Vectorizer (Theory).ko_KR.vtt 15.9 KB
11 - Text Summarization/8 -TextRank in Python (Advanced).vtt 15.0 KB
9 - Spam Detection/4 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).vtt 14.7 KB
22 - Effective Learning Strategies for Machine Learning FAQ/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).vtt 14.5 KB
11 - Text Summarization/subtitles/8 -TextRank in Python (Advanced).ko_KR.vtt 14.5 KB
5 - Markov Models (Intermediate)/3 -The Markov Model.vtt 14.3 KB
9 - Spam Detection/subtitles/4 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).ko_KR.vtt 14.2 KB
22 - Effective Learning Strategies for Machine Learning FAQ/subtitles/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).ko_KR.vtt 14.1 KB
21 - Extra Help With Python Coding for Beginners FAQ/subtitles/6 -How to use Github & Extra Coding Tips (Optional).ko_KR.vtt 13.9 KB
3 - Vector Models and Text Preprocessing/8 -Stemming and Lemmatization.vtt 13.9 KB
21 - Extra Help With Python Coding for Beginners FAQ/6 -How to use Github & Extra Coding Tips (Optional).vtt 13.8 KB
3 - Vector Models and Text Preprocessing/subtitles/8 -Stemming and Lemmatization.ko_KR.vtt 13.7 KB
5 - Markov Models (Intermediate)/subtitles/3 -The Markov Model.ko_KR.vtt 13.7 KB
1 - Introduction/1 -Introduction and Outline.vtt 13.7 KB
13 - Latent Semantic Analysis (Latent Semantic Indexing)/2 -SVD (Singular Value Decomposition) Intuition.vtt 13.5 KB
12 - Topic Modeling/subtitles/2 -Latent Dirichlet Allocation (LDA) - Essentials.ko_KR.vtt 13.5 KB
3 - Vector Models and Text Preprocessing/subtitles/15 -Word-to-Index Mapping.ko_KR.vtt 13.4 KB
1 - Introduction/subtitles/1 -Introduction and Outline.ko_KR.vtt 13.4 KB
11 - Text Summarization/subtitles/4 -Text Summarization in Python.ko_KR.vtt 13.4 KB
9 - Spam Detection/2 -Naive Bayes Intuition.vtt 13.3 KB
12 - Topic Modeling/2 -Latent Dirichlet Allocation (LDA) - Essentials.vtt 13.3 KB
3 - Vector Models and Text Preprocessing/11 -Vector Similarity.vtt 13.3 KB
11 - Text Summarization/4 -Text Summarization in Python.vtt 13.2 KB
18 - Recurrent Neural Networks/7 -GRU and LSTM (pt 2).vtt 13.2 KB
9 - Spam Detection/subtitles/2 -Naive Bayes Intuition.ko_KR.vtt 13.1 KB
3 - Vector Models and Text Preprocessing/3 -What is a Vector.vtt 13.0 KB
16 - Feedforward Artificial Neural Networks/8 -Text Preprocessing Code Preparation.vtt 13.0 KB
16 - Feedforward Artificial Neural Networks/subtitles/8 -Text Preprocessing Code Preparation.ko_KR.vtt 13.0 KB
20 - Setting Up Your Environment FAQ/subtitles/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.ko_KR.vtt 13.0 KB
3 - Vector Models and Text Preprocessing/15 -Word-to-Index Mapping.vtt 12.9 KB
3 - Vector Models and Text Preprocessing/subtitles/3 -What is a Vector.ko_KR.vtt 12.9 KB
22 - Effective Learning Strategies for Machine Learning FAQ/1 -How to Succeed in this Course (Long Version).vtt 12.8 KB
13 - Latent Semantic Analysis (Latent Semantic Indexing)/subtitles/2 -SVD (Singular Value Decomposition) Intuition.ko_KR.vtt 12.8 KB
3 - Vector Models and Text Preprocessing/subtitles/21 -How To Do NLP In Other Languages.ko_KR.vtt 12.8 KB
3 - Vector Models and Text Preprocessing/21 -How To Do NLP In Other Languages.vtt 12.7 KB
9 - Spam Detection/5 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).vtt 12.6 KB
22 - Effective Learning Strategies for Machine Learning FAQ/subtitles/1 -How to Succeed in this Course (Long Version).ko_KR.vtt 12.6 KB
20 - Setting Up Your Environment FAQ/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12.6 KB
15 - The Neuron/6 -How does a model learn.vtt 12.6 KB
3 - Vector Models and Text Preprocessing/subtitles/11 -Vector Similarity.ko_KR.vtt 12.5 KB
18 - Recurrent Neural Networks/subtitles/7 -GRU and LSTM (pt 2).ko_KR.vtt 12.5 KB
21 - Extra Help With Python Coding for Beginners FAQ/3 -Proof that using Jupyter Notebook is the same as not using it.vtt 12.4 KB
21 - Extra Help With Python Coding for Beginners FAQ/subtitles/3 -Proof that using Jupyter Notebook is the same as not using it.ko_KR.vtt 12.3 KB
15 - The Neuron/subtitles/6 -How does a model learn.ko_KR.vtt 12.2 KB
9 - Spam Detection/subtitles/5 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).ko_KR.vtt 12.2 KB
3 - Vector Models and Text Preprocessing/9 -Stemming and Lemmatization Demo.vtt 12.1 KB
12 - Topic Modeling/7 -Non-Negative Matrix Factorization (NMF) Intuition.vtt 12.1 KB
5 - Markov Models (Intermediate)/8 -Building a Text Classifier (Code pt 2).vtt 12.1 KB
5 - Markov Models (Intermediate)/subtitles/8 -Building a Text Classifier (Code pt 2).ko_KR.vtt 12.1 KB
11 - Text Summarization/6 -TextRank - How It Really Works (Advanced).vtt 11.9 KB
12 - Topic Modeling/subtitles/6 -Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.ko_KR.vtt 11.9 KB
3 - Vector Models and Text Preprocessing/subtitles/9 -Stemming and Lemmatization Demo.ko_KR.vtt 11.9 KB
12 - Topic Modeling/subtitles/7 -Non-Negative Matrix Factorization (NMF) Intuition.ko_KR.vtt 11.9 KB
3 - Vector Models and Text Preprocessing/17 -Neural Word Embeddings.vtt 11.8 KB
5 - Markov Models (Intermediate)/9 -Language Model (Theory).vtt 11.7 KB
21 - Extra Help With Python Coding for Beginners FAQ/2 -How to Code by Yourself (part 2).vtt 11.7 KB
12 - Topic Modeling/6 -Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.vtt 11.6 KB
11 - Text Summarization/subtitles/6 -TextRank - How It Really Works (Advanced).ko_KR.vtt 11.6 KB
5 - Markov Models (Intermediate)/11 -Language Model (Code pt 1).vtt 11.6 KB
3 - Vector Models and Text Preprocessing/subtitles/17 -Neural Word Embeddings.ko_KR.vtt 11.5 KB
18 - Recurrent Neural Networks/3 -Simple RNN Elman Unit (pt 2).vtt 11.4 KB
5 - Markov Models (Intermediate)/subtitles/9 -Language Model (Theory).ko_KR.vtt 11.3 KB
5 - Markov Models (Intermediate)/subtitles/11 -Language Model (Code pt 1).ko_KR.vtt 11.3 KB
21 - Extra Help With Python Coding for Beginners FAQ/subtitles/2 -How to Code by Yourself (part 2).ko_KR.vtt 11.2 KB
18 - Recurrent Neural Networks/subtitles/3 -Simple RNN Elman Unit (pt 2).ko_KR.vtt 11.2 KB
18 - Recurrent Neural Networks/subtitles/4 -RNN Code Preparation.ko_KR.vtt 11.1 KB
15 - The Neuron/5 -The Neuron.vtt 11.1 KB
3 - Vector Models and Text Preprocessing/18 -Neural Word Embeddings Demo.vtt 11.1 KB
16 - Feedforward Artificial Neural Networks/10 -Embeddings.vtt 11.1 KB
18 - Recurrent Neural Networks/4 -RNN Code Preparation.vtt 11.1 KB
16 - Feedforward Artificial Neural Networks/subtitles/10 -Embeddings.ko_KR.vtt 11.0 KB
16 - Feedforward Artificial Neural Networks/2 -Forward Propagation.vtt 11.0 KB
3 - Vector Models and Text Preprocessing/subtitles/18 -Neural Word Embeddings Demo.ko_KR.vtt 10.9 KB
6 - Article Spinner (Intermediate)/5 -Article Spinner in Python (pt 2).vtt 10.9 KB
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10 - Sentiment Analysis/subtitles/1 -Sentiment Analysis - Problem Description.ko_KR.vtt 8.6 KB
10 - Sentiment Analysis/subtitles/7 -Sentiment Analysis in Python (pt 2).ko_KR.vtt 8.6 KB
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5 - Markov Models (Intermediate)/2 -The Markov Property.vtt 8.3 KB
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7 - Cipher Decryption (Advanced)/subtitles/7 -Code pt 2.ko_KR.vtt 8.1 KB
19 - Course Conclusion/subtitles/1 -What to Learn Next.ko_KR.vtt 8.0 KB
19 - Course Conclusion/1 -What to Learn Next.vtt 8.0 KB
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9 - Spam Detection/subtitles/1 -Spam Detection - Problem Description.ko_KR.vtt 7.9 KB
16 - Feedforward Artificial Neural Networks/subtitles/1 -ANN - Section Introduction.ko_KR.vtt 7.9 KB
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16 - Feedforward Artificial Neural Networks/15 -Aside How to Choose Hyperparameters (Optional).vtt 7.5 KB
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23 - Appendix FAQ Finale/subtitles/2 -BONUS.ko_KR.vtt 7.3 KB
16 - Feedforward Artificial Neural Networks/subtitles/15 -Aside How to Choose Hyperparameters (Optional).ko_KR.vtt 7.3 KB
7 - Cipher Decryption (Advanced)/14 -Section Conclusion.vtt 7.3 KB
7 - Cipher Decryption (Advanced)/subtitles/14 -Section Conclusion.ko_KR.vtt 7.1 KB
8 - Machine Learning Models (Introduction)/subtitles/1 -Machine Learning Models (Introduction).ko_KR.vtt 7.1 KB
17 - Convolutional Neural Networks/4 -What is Convolution (Weight Sharing).vtt 7.0 KB
17 - Convolutional Neural Networks/subtitles/4 -What is Convolution (Weight Sharing).ko_KR.vtt 6.9 KB
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13 - Latent Semantic Analysis (Latent Semantic Indexing)/5 -LSA LSI Exercises.vtt 6.5 KB
11 - Text Summarization/2 -Text Summarization Using Vectors.vtt 6.4 KB
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2 - Getting Set Up/1 -Where To Get the Code.vtt 6.0 KB
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18 - Recurrent Neural Networks/1 -RNN - Section Introduction.vtt 5.6 KB
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3 - Vector Models and Text Preprocessing/7 -Stopwords.vtt 5.5 KB
16 - Feedforward Artificial Neural Networks/9 -Text Preprocessing in Tensorflow.vtt 5.5 KB
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16 - Feedforward Artificial Neural Networks/6 -ANN Code Preparation.vtt 5.3 KB
17 - Convolutional Neural Networks/1 -CNN - Section Introduction.vtt 5.2 KB
21 - Extra Help With Python Coding for Beginners FAQ/subtitles/5 -Where To Get the Code Troubleshooting.ko_KR.vtt 5.1 KB
17 - Convolutional Neural Networks/subtitles/1 -CNN - Section Introduction.ko_KR.vtt 5.1 KB
21 - Extra Help With Python Coding for Beginners FAQ/5 -Where To Get the Code Troubleshooting.vtt 5.1 KB
18 - Recurrent Neural Networks/subtitles/8 -RNN for Text Classification in Tensorflow.ko_KR.vtt 5.0 KB
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12 - Topic Modeling/8 -Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.vtt 4.3 KB
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3 - Vector Models and Text Preprocessing/22 -Suggestion Box.vtt 4.1 KB
7 - Cipher Decryption (Advanced)/subtitles/2 -Ciphers.ko_KR.vtt 4.1 KB
3 - Vector Models and Text Preprocessing/subtitles/22 -Suggestion Box.ko_KR.vtt 4.0 KB
2 - Getting Set Up/2 -How to Succeed in This Course.vtt 3.9 KB
11 - Text Summarization/10 -Text Summarization Section Summary.vtt 3.9 KB
2 - Getting Set Up/subtitles/2 -How to Succeed in This Course.ko_KR.vtt 3.9 KB
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Udemy - Machine Learning Natural Language Processing in Python (V2) (12.2024)

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