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

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

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收录时间：2025-07-07
最近下载：2025-09-27

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文件列表

  • 18 - Recurrent Neural Networks/9 -Parts-of-Speech (POS) Tagging in Tensorflow.mp4 152.1 MB
  • 3 - Vector Models and Text Preprocessing/14 -TF-IDF (Code).mp4 131.0 MB
  • 16 - Feedforward Artificial Neural Networks/13 -CBOW in Tensorflow (Advanced).mp4 123.3 MB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 113.4 MB
  • 9 - Spam Detection/6 -Spam Detection in Python.mp4 112.8 MB
  • 7 - Cipher Decryption (Advanced)/4 -Genetic Algorithms.mp4 110.3 MB
  • 3 - Vector Models and Text Preprocessing/10 -Count Vectorizer (Code).mp4 106.9 MB
  • 6 - Article Spinner (Intermediate)/4 -Article Spinner in Python (pt 1).mp4 100.6 MB
  • 16 - Feedforward Artificial Neural Networks/4 -Activation Functions.mp4 93.7 MB
  • 17 - Convolutional Neural Networks/6 -CNN Architecture.mp4 93.6 MB
  • 11 - Text Summarization/8 -TextRank in Python (Advanced).mp4 86.3 MB
  • 18 - Recurrent Neural Networks/6 -GRU and LSTM (pt 1).mp4 86.2 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/2 -SVD (Singular Value Decomposition) Intuition.mp4 85.8 MB
  • 15 - The Neuron/4 -Text Classification in Tensorflow.mp4 85.6 MB
  • 17 - Convolutional Neural Networks/2 -What is Convolution.mp4 83.7 MB
  • 3 - Vector Models and Text Preprocessing/16 -How to Build TF-IDF From Scratch.mp4 83.7 MB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 83.5 MB
  • 11 - Text Summarization/4 -Text Summarization in Python.mp4 81.9 MB
  • 6 - Article Spinner (Intermediate)/5 -Article Spinner in Python (pt 2).mp4 79.0 MB
  • 17 - Convolutional Neural Networks/5 -Convolution on Color Images.mp4 78.8 MB
  • 3 - Vector Models and Text Preprocessing/9 -Stemming and Lemmatization Demo.mp4 78.5 MB
  • 3 - Vector Models and Text Preprocessing/6 -Tokenization.mp4 77.1 MB
  • 1 - Introduction/1 -Introduction and Outline.mp4 76.5 MB
  • 12 - Topic Modeling/6 -Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4 75.9 MB
  • 5 - Markov Models (Intermediate)/8 -Building a Text Classifier (Code pt 2).mp4 75.7 MB
  • 21 - Extra Help With Python Coding for Beginners FAQ/1 -How to Code by Yourself (part 1).mp4 75.3 MB
  • 21 - Extra Help With Python Coding for Beginners FAQ/3 -Proof that using Jupyter Notebook is the same as not using it.mp4 72.8 MB
  • 15 - The Neuron/2 -Fitting a Line.mp4 71.9 MB
  • 3 - Vector Models and Text Preprocessing/18 -Neural Word Embeddings Demo.mp4 70.1 MB
  • 7 - Cipher Decryption (Advanced)/3 -Language Models (Review).mp4 68.7 MB
  • 21 - Extra Help With Python Coding for Beginners FAQ/6 -How to use Github & Extra Coding Tips (Optional).mp4 67.0 MB
  • 10 - Sentiment Analysis/2 -Logistic Regression Intuition (pt 1).mp4 66.7 MB
  • 10 - Sentiment Analysis/6 -Sentiment Analysis in Python (pt 1).mp4 66.2 MB
  • 5 - Markov Models (Intermediate)/11 -Language Model (Code pt 1).mp4 65.9 MB
  • 9 - Spam Detection/4 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 63.1 MB
  • 12 - Topic Modeling/5 -Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4 63.1 MB
  • 3 - Vector Models and Text Preprocessing/12 -TF-IDF (Theory).mp4 61.4 MB
  • 3 - Vector Models and Text Preprocessing/8 -Stemming and Lemmatization.mp4 60.7 MB
  • 5 - Markov Models (Intermediate)/7 -Building a Text Classifier (Code pt 1).mp4 60.5 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/4 -Latent Semantic Analysis Latent Semantic Indexing in Python.mp4 60.3 MB
  • 3 - Vector Models and Text Preprocessing/5 -Count Vectorizer (Theory).mp4 60.2 MB
  • 18 - Recurrent Neural Networks/5 -RNNs Paying Attention to Shapes.mp4 59.9 MB
  • 16 - Feedforward Artificial Neural Networks/3 -The Geometrical Picture.mp4 59.3 MB
  • 3 - Vector Models and Text Preprocessing/21 -How To Do NLP In Other Languages.mp4 58.7 MB
  • 12 - Topic Modeling/2 -Latent Dirichlet Allocation (LDA) - Essentials.mp4 57.9 MB
  • 9 - Spam Detection/5 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 56.6 MB
  • 20 - Setting Up Your Environment FAQ/2 -Anaconda Environment Setup.mp4 55.2 MB
  • 12 - Topic Modeling/7 -Non-Negative Matrix Factorization (NMF) Intuition.mp4 55.0 MB
  • 5 - Markov Models (Intermediate)/12 -Language Model (Code pt 2).mp4 55.0 MB
  • 10 - Sentiment Analysis/7 -Sentiment Analysis in Python (pt 2).mp4 54.5 MB
  • 15 - The Neuron/6 -How does a model learn.mp4 54.1 MB
  • 9 - Spam Detection/2 -Naive Bayes Intuition.mp4 53.8 MB
  • 20 - Setting Up Your Environment FAQ/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 53.4 MB
  • 18 - Recurrent Neural Networks/7 -GRU and LSTM (pt 2).mp4 52.8 MB
  • 16 - Feedforward Artificial Neural Networks/8 -Text Preprocessing Code Preparation.mp4 52.4 MB
  • 11 - Text Summarization/6 -TextRank - How It Really Works (Advanced).mp4 51.7 MB
  • 21 - Extra Help With Python Coding for Beginners FAQ/2 -How to Code by Yourself (part 2).mp4 51.5 MB
  • 3 - Vector Models and Text Preprocessing/3 -What is a Vector.mp4 51.3 MB
  • 3 - Vector Models and Text Preprocessing/15 -Word-to-Index Mapping.mp4 49.9 MB
  • 16 - Feedforward Artificial Neural Networks/2 -Forward Propagation.mp4 49.0 MB
  • 11 - Text Summarization/5 -TextRank Intuition.mp4 48.2 MB
  • 18 - Recurrent Neural Networks/8 -RNN for Text Classification in Tensorflow.mp4 48.1 MB
  • 5 - Markov Models (Intermediate)/3 -The Markov Model.mp4 48.1 MB
  • 3 - Vector Models and Text Preprocessing/17 -Neural Word Embeddings.mp4 47.8 MB
  • 15 - The Neuron/5 -The Neuron.mp4 47.4 MB
  • 11 - Text Summarization/9 -Text Summarization in Python - The Easy Way (Beginner).mp4 47.4 MB
  • 3 - Vector Models and Text Preprocessing/11 -Vector Similarity.mp4 47.3 MB
  • 5 - Markov Models (Intermediate)/9 -Language Model (Theory).mp4 47.1 MB
  • 16 - Feedforward Artificial Neural Networks/5 -Multiclass Classification.mp4 46.6 MB
  • 21 - Extra Help With Python Coding for Beginners FAQ/4 -Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 45.7 MB
  • 19 - Course Conclusion/2 -Where is BERT, ChatGPT, GPT-4,.mp4 44.9 MB
  • 10 - Sentiment Analysis/1 -Sentiment Analysis - Problem Description.mp4 44.8 MB
  • 16 - Feedforward Artificial Neural Networks/10 -Embeddings.mp4 44.3 MB
  • 18 - Recurrent Neural Networks/4 -RNN Code Preparation.mp4 44.2 MB
  • 17 - Convolutional Neural Networks/8 -Convolutional Neural Network for NLP in Tensorflow.mp4 44.1 MB
  • 6 - Article Spinner (Intermediate)/1 -Article Spinning - Problem Description.mp4 44.0 MB
  • 18 - Recurrent Neural Networks/3 -Simple RNN Elman Unit (pt 2).mp4 43.2 MB
  • 7 - Cipher Decryption (Advanced)/10 -Code pt 5.mp4 42.9 MB
  • 18 - Recurrent Neural Networks/2 -Simple RNN Elman Unit (pt 1).mp4 42.8 MB
  • 17 - Convolutional Neural Networks/7 -CNNs for Text.mp4 42.4 MB
  • 23 - Appendix FAQ Finale/2 -BONUS.mp4 42.4 MB
  • 10 - Sentiment Analysis/4 -Logistic Regression Training and Interpretation (pt 3).mp4 41.6 MB
  • 7 - Cipher Decryption (Advanced)/11 -Code pt 6.mp4 41.3 MB
  • 7 - Cipher Decryption (Advanced)/7 -Code pt 2.mp4 41.0 MB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
  • 16 - Feedforward Artificial Neural Networks/1 -ANN - Section Introduction.mp4 40.5 MB
  • 16 - Feedforward Artificial Neural Networks/15 -Aside How to Choose Hyperparameters (Optional).mp4 39.9 MB
  • 19 - Course Conclusion/1 -What to Learn Next.mp4 39.2 MB
  • 16 - Feedforward Artificial Neural Networks/7 -Text Classification ANN in Tensorflow.mp4 37.9 MB
  • 12 - Topic Modeling/8 -Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp4 37.8 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/3 -LSA LSI Applying SVD to NLP.mp4 36.1 MB
  • 5 - Markov Models (Intermediate)/4 -Probability Smoothing and Log-Probabilities.mp4 35.7 MB
  • 15 - The Neuron/3 -Classification Code Preparation.mp4 34.5 MB
  • 5 - Markov Models (Intermediate)/2 -The Markov Property.mp4 33.8 MB
  • 18 - Recurrent Neural Networks/10 -Named Entity Recognition (NER) in Tensorflow.mp4 33.1 MB
  • 9 - Spam Detection/1 -Spam Detection - Problem Description.mp4 32.9 MB
  • 16 - Feedforward Artificial Neural Networks/9 -Text Preprocessing in Tensorflow.mp4 32.4 MB
  • 17 - Convolutional Neural Networks/4 -What is Convolution (Weight Sharing).mp4 31.3 MB
  • 8 - Machine Learning Models (Introduction)/1 -Machine Learning Models (Introduction).mp4 31.0 MB
  • 7 - Cipher Decryption (Advanced)/8 -Code pt 3.mp4 31.0 MB
  • 5 - Markov Models (Intermediate)/6 -Building a Text Classifier (Exercise Prompt).mp4 30.8 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/5 -LSA LSI Exercises.mp4 30.5 MB
  • 5 - Markov Models (Intermediate)/5 -Building a Text Classifier (Theory).mp4 30.3 MB
  • 5 - Markov Models (Intermediate)/10 -Language Model (Exercise Prompt).mp4 30.2 MB
  • 3 - Vector Models and Text Preprocessing/2 -Basic Definitions for NLP.mp4 29.7 MB
  • 6 - Article Spinner (Intermediate)/6 -Case Study Article Spinning Gone Wrong.mp4 29.6 MB
  • 3 - Vector Models and Text Preprocessing/22 -Suggestion Box.mp4 28.5 MB
  • 4 - Probabilistic Models (Introduction)/1 -Probabilistic Models (Introduction).mp4 28.2 MB
  • 1 - Introduction/2 -Are You Beginner, Intermediate, or Advanced All are OK!.mp4 28.0 MB
  • 7 - Cipher Decryption (Advanced)/1 -Section Introduction.mp4 27.6 MB
  • 11 - Text Summarization/2 -Text Summarization Using Vectors.mp4 27.0 MB
  • 11 - Text Summarization/1 -Text Summarization Section Introduction.mp4 27.0 MB
  • 7 - Cipher Decryption (Advanced)/9 -Code pt 4.mp4 26.9 MB
  • 17 - Convolutional Neural Networks/1 -CNN - Section Introduction.mp4 26.9 MB
  • 6 - Article Spinner (Intermediate)/3 -Article Spinner Exercise Prompt.mp4 25.8 MB
  • 17 - Convolutional Neural Networks/3 -What is Convolution (Pattern Matching).mp4 25.8 MB
  • 14 - Deep Learning (Introduction)/1 -Deep Learning Introduction (Intermediate-Advanced).mp4 25.7 MB
  • 21 - Extra Help With Python Coding for Beginners FAQ/5 -Where To Get the Code Troubleshooting.mp4 25.5 MB
  • 7 - Cipher Decryption (Advanced)/14 -Section Conclusion.mp4 25.4 MB
  • 10 - Sentiment Analysis/3 -Multiclass Logistic Regression (pt 2).mp4 24.8 MB
  • 3 - Vector Models and Text Preprocessing/7 -Stopwords.mp4 24.6 MB
  • 20 - Setting Up Your Environment FAQ/1 -Pre-Installation Check.mp4 23.9 MB
  • 2 - Getting Set Up/1 -Where To Get the Code.mp4 23.6 MB
  • 2 - Getting Set Up/3 -Temporary 403 Errors.mp4 23.1 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/1 -LSA LSI Section Introduction.mp4 22.0 MB
  • 18 - Recurrent Neural Networks/1 -RNN - Section Introduction.mp4 21.9 MB
  • 3 - Vector Models and Text Preprocessing/19 -Vector Models & Text Preprocessing Summary.mp4 21.9 MB
  • 7 - Cipher Decryption (Advanced)/5 -Code Preparation.mp4 21.6 MB
  • 16 - Feedforward Artificial Neural Networks/6 -ANN Code Preparation.mp4 21.1 MB
  • 11 - Text Summarization/10 -Text Summarization Section Summary.mp4 21.1 MB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/1 -How to Succeed in this Course (Long Version).mp4 18.7 MB
  • 7 - Cipher Decryption (Advanced)/13 -Real-World Application Acoustic Keylogger.mp4 18.5 MB
  • 3 - Vector Models and Text Preprocessing/1 -Vector Models & Text Preprocessing Intro.mp4 18.4 MB
  • 7 - Cipher Decryption (Advanced)/2 -Ciphers.mp4 18.0 MB
  • 12 - Topic Modeling/1 -Topic Modeling Section Introduction.mp4 17.9 MB
  • 10 - Sentiment Analysis/5 -Sentiment Analysis - Exercise Prompt.mp4 17.4 MB
  • 23 - Appendix FAQ Finale/1 -What is the Appendix.mp4 17.2 MB
  • 2 - Getting Set Up/2 -How to Succeed in This Course.mp4 17.1 MB
  • 7 - Cipher Decryption (Advanced)/6 -Code pt 1.mp4 16.8 MB
  • 6 - Article Spinner (Intermediate)/2 -Article Spinning - N-Gram Approach.mp4 16.7 MB
  • 16 - Feedforward Artificial Neural Networks/11 -CBOW (Advanced).mp4 16.5 MB
  • 5 - Markov Models (Intermediate)/13 -Markov Models Section Summary.mp4 16.3 MB
  • 7 - Cipher Decryption (Advanced)/12 -Cipher Decryption - Additional Discussion.mp4 15.4 MB
  • 18 - Recurrent Neural Networks/11 -Exercise Return to CNNs (Advanced).mp4 15.3 MB
  • 12 - Topic Modeling/3 -LDA - Code Preparation.mp4 15.2 MB
  • 3 - Vector Models and Text Preprocessing/4 -Bag of Words.mp4 14.5 MB
  • 3 - Vector Models and Text Preprocessing/13 -(Interactive) Recommender Exercise Prompt.mp4 14.0 MB
  • 5 - Markov Models (Intermediate)/1 -Markov Models Section Introduction.mp4 13.7 MB
  • 15 - The Neuron/1 -The Neuron - Section Introduction.mp4 11.5 MB
  • 15 - The Neuron/7 -The Neuron - Section Summary.mp4 10.8 MB
  • 12 - Topic Modeling/9 -Topic Modeling Section Summary.mp4 10.3 MB
  • 18 - Recurrent Neural Networks/12 -RNN - Section Summary.mp4 9.5 MB
  • 12 - Topic Modeling/4 -LDA - Maybe Useful Picture (Optional).mp4 9.4 MB
  • 9 - Spam Detection/3 -Spam Detection - Exercise Prompt.mp4 9.2 MB
  • 17 - Convolutional Neural Networks/9 -CNN - Section Summary.mp4 8.6 MB
  • 11 - Text Summarization/3 -Text Summarization Exercise Prompt.mp4 8.5 MB
  • 16 - Feedforward Artificial Neural Networks/14 -ANN - Section Summary.mp4 8.0 MB
  • 11 - Text Summarization/7 -TextRank Exercise Prompt (Advanced).mp4 7.8 MB
  • 3 - Vector Models and Text Preprocessing/20 -Text Summarization Preview.mp4 6.6 MB
  • 16 - Feedforward Artificial Neural Networks/12 -CBOW Exercise Prompt.mp4 5.3 MB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 29.0 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 28.1 kB
  • 7 - Cipher Decryption (Advanced)/4 -Genetic Algorithms.vtt 26.1 kB
  • 17 - Convolutional Neural Networks/6 -CNN Architecture.vtt 25.6 kB
  • 7 - Cipher Decryption (Advanced)/subtitles/4 -Genetic Algorithms.ko_KR.vtt 25.3 kB
  • 17 - Convolutional Neural Networks/subtitles/6 -CNN Architecture.ko_KR.vtt 25.1 kB
  • 3 - Vector Models and Text Preprocessing/14 -TF-IDF (Code).vtt 22.1 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/14 -TF-IDF (Code).ko_KR.vtt 21.6 kB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).vtt 21.2 kB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/subtitles/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).ko_KR.vtt 21.0 kB
  • 18 - Recurrent Neural Networks/6 -GRU and LSTM (pt 1).vtt 20.7 kB
  • 16 - Feedforward Artificial Neural Networks/4 -Activation Functions.vtt 20.5 kB
  • 18 - Recurrent Neural Networks/subtitles/9 -Parts-of-Speech (POS) Tagging in Tensorflow.ko_KR.vtt 20.4 kB
  • 21 - Extra Help With Python Coding for Beginners FAQ/1 -How to Code by Yourself (part 1).vtt 20.3 kB
  • 18 - Recurrent Neural Networks/9 -Parts-of-Speech (POS) Tagging in Tensorflow.vtt 20.3 kB
  • 10 - Sentiment Analysis/2 -Logistic Regression Intuition (pt 1).vtt 20.2 kB
  • 18 - Recurrent Neural Networks/subtitles/6 -GRU and LSTM (pt 1).ko_KR.vtt 19.9 kB
  • 16 - Feedforward Artificial Neural Networks/subtitles/4 -Activation Functions.ko_KR.vtt 19.7 kB
  • 10 - Sentiment Analysis/subtitles/2 -Logistic Regression Intuition (pt 1).ko_KR.vtt 19.3 kB
  • 21 - Extra Help With Python Coding for Beginners FAQ/subtitles/1 -How to Code by Yourself (part 1).ko_KR.vtt 19.3 kB
  • 17 - Convolutional Neural Networks/5 -Convolution on Color Images.vtt 18.7 kB
  • 16 - Feedforward Artificial Neural Networks/subtitles/13 -CBOW in Tensorflow (Advanced).ko_KR.vtt 18.6 kB
  • 20 - Setting Up Your Environment FAQ/subtitles/2 -Anaconda Environment Setup.ko_KR.vtt 18.5 kB
  • 6 - Article Spinner (Intermediate)/4 -Article Spinner in Python (pt 1).vtt 18.5 kB
  • 17 - Convolutional Neural Networks/2 -What is Convolution.vtt 18.5 kB
  • 17 - Convolutional Neural Networks/subtitles/2 -What is Convolution.ko_KR.vtt 18.4 kB
  • 7 - Cipher Decryption (Advanced)/3 -Language Models (Review).vtt 18.4 kB
  • 6 - Article Spinner (Intermediate)/subtitles/4 -Article Spinner in Python (pt 1).ko_KR.vtt 18.4 kB
  • 16 - Feedforward Artificial Neural Networks/13 -CBOW in Tensorflow (Advanced).vtt 18.2 kB
  • 12 - Topic Modeling/5 -Latent Dirichlet Allocation (LDA) - Intuition (Advanced).vtt 18.1 kB
  • 12 - Topic Modeling/subtitles/5 -Latent Dirichlet Allocation (LDA) - Intuition (Advanced).ko_KR.vtt 18.0 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/6 -Tokenization.ko_KR.vtt 18.0 kB
  • 20 - Setting Up Your Environment FAQ/2 -Anaconda Environment Setup.vtt 17.8 kB
  • 3 - Vector Models and Text Preprocessing/6 -Tokenization.vtt 17.8 kB
  • 17 - Convolutional Neural Networks/subtitles/5 -Convolution on Color Images.ko_KR.vtt 17.7 kB
  • 9 - Spam Detection/6 -Spam Detection in Python.vtt 17.2 kB
  • 3 - Vector Models and Text Preprocessing/5 -Count Vectorizer (Theory).vtt 17.2 kB
  • 3 - Vector Models and Text Preprocessing/10 -Count Vectorizer (Code).vtt 17.1 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/10 -Count Vectorizer (Code).ko_KR.vtt 17.0 kB
  • 9 - Spam Detection/subtitles/6 -Spam Detection in Python.ko_KR.vtt 16.9 kB
  • 7 - Cipher Decryption (Advanced)/subtitles/3 -Language Models (Review).ko_KR.vtt 16.8 kB
  • 15 - The Neuron/subtitles/2 -Fitting a Line.ko_KR.vtt 16.7 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/16 -How to Build TF-IDF From Scratch.ko_KR.vtt 16.6 kB
  • 3 - Vector Models and Text Preprocessing/16 -How to Build TF-IDF From Scratch.vtt 16.6 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/12 -TF-IDF (Theory).ko_KR.vtt 16.5 kB
  • 15 - The Neuron/2 -Fitting a Line.vtt 16.5 kB
  • 3 - Vector Models and Text Preprocessing/12 -TF-IDF (Theory).vtt 16.4 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/5 -Count Vectorizer (Theory).ko_KR.vtt 16.3 kB
  • 11 - Text Summarization/8 -TextRank in Python (Advanced).vtt 15.3 kB
  • 9 - Spam Detection/4 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).vtt 15.1 kB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).vtt 14.9 kB
  • 11 - Text Summarization/subtitles/8 -TextRank in Python (Advanced).ko_KR.vtt 14.9 kB
  • 5 - Markov Models (Intermediate)/3 -The Markov Model.vtt 14.7 kB
  • 9 - Spam Detection/subtitles/4 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).ko_KR.vtt 14.5 kB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/subtitles/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).ko_KR.vtt 14.5 kB
  • 21 - Extra Help With Python Coding for Beginners FAQ/subtitles/6 -How to use Github & Extra Coding Tips (Optional).ko_KR.vtt 14.3 kB
  • 3 - Vector Models and Text Preprocessing/8 -Stemming and Lemmatization.vtt 14.2 kB
  • 21 - Extra Help With Python Coding for Beginners FAQ/6 -How to use Github & Extra Coding Tips (Optional).vtt 14.1 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/8 -Stemming and Lemmatization.ko_KR.vtt 14.0 kB
  • 5 - Markov Models (Intermediate)/subtitles/3 -The Markov Model.ko_KR.vtt 14.0 kB
  • 1 - Introduction/1 -Introduction and Outline.vtt 14.0 kB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/2 -SVD (Singular Value Decomposition) Intuition.vtt 13.8 kB
  • 12 - Topic Modeling/subtitles/2 -Latent Dirichlet Allocation (LDA) - Essentials.ko_KR.vtt 13.8 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/15 -Word-to-Index Mapping.ko_KR.vtt 13.7 kB
  • 1 - Introduction/subtitles/1 -Introduction and Outline.ko_KR.vtt 13.7 kB
  • 11 - Text Summarization/subtitles/4 -Text Summarization in Python.ko_KR.vtt 13.7 kB
  • 9 - Spam Detection/2 -Naive Bayes Intuition.vtt 13.7 kB
  • 12 - Topic Modeling/2 -Latent Dirichlet Allocation (LDA) - Essentials.vtt 13.7 kB
  • 3 - Vector Models and Text Preprocessing/11 -Vector Similarity.vtt 13.6 kB
  • 11 - Text Summarization/4 -Text Summarization in Python.vtt 13.5 kB
  • 18 - Recurrent Neural Networks/7 -GRU and LSTM (pt 2).vtt 13.5 kB
  • 9 - Spam Detection/subtitles/2 -Naive Bayes Intuition.ko_KR.vtt 13.4 kB
  • 3 - Vector Models and Text Preprocessing/3 -What is a Vector.vtt 13.4 kB
  • 16 - Feedforward Artificial Neural Networks/8 -Text Preprocessing Code Preparation.vtt 13.4 kB
  • 16 - Feedforward Artificial Neural Networks/subtitles/8 -Text Preprocessing Code Preparation.ko_KR.vtt 13.3 kB
  • 20 - Setting Up Your Environment FAQ/subtitles/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.ko_KR.vtt 13.3 kB
  • 3 - Vector Models and Text Preprocessing/15 -Word-to-Index Mapping.vtt 13.2 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/3 -What is a Vector.ko_KR.vtt 13.2 kB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/1 -How to Succeed in this Course (Long Version).vtt 13.1 kB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/subtitles/2 -SVD (Singular Value Decomposition) Intuition.ko_KR.vtt 13.1 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/21 -How To Do NLP In Other Languages.ko_KR.vtt 13.1 kB
  • 3 - Vector Models and Text Preprocessing/21 -How To Do NLP In Other Languages.vtt 13.1 kB
  • 9 - Spam Detection/5 -Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).vtt 12.9 kB
  • 22 - Effective Learning Strategies for Machine Learning FAQ/subtitles/1 -How to Succeed in this Course (Long Version).ko_KR.vtt 12.9 kB
  • 20 - Setting Up Your Environment FAQ/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12.9 kB
  • 15 - The Neuron/6 -How does a model learn.vtt 12.9 kB
  • 3 - Vector Models and Text Preprocessing/subtitles/11 -Vector Similarity.ko_KR.vtt 12.8 kB
  • 18 - Recurrent Neural Networks/subtitles/7 -GRU and LSTM (pt 2).ko_KR.vtt 12.8 kB
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  • 15 - The Neuron/5 -The Neuron.vtt 11.4 kB
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  • 16 - Feedforward Artificial Neural Networks/12 -CBOW Exercise Prompt.vtt 883 Bytes
  • 21 - Extra Help With Python Coding for Beginners FAQ/4 -Data Links.url 119 Bytes
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  • 2 - Getting Set Up/1 -Code Link.url 87 Bytes

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