[GigaCourse.Com] Udemy - Machine Learning Natural Language Processing in Python (V2)

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[GigaCourse.Com] Udemy - Machine Learning Natural Language Processing in Python (V2)

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收录时间：2023-12-25
最近下载：2024-10-15

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文件列表

  • 18 - Recurrent Neural Networks/009 Parts-of-Speech (POS) Tagging in Tensorflow.mp4 152.1 MB
  • 03 - Vector Models and Text Preprocessing/014 TF-IDF (Code).mp4 131.0 MB
  • 16 - Feedforward Artificial Neural Networks/013 CBOW in Tensorflow (Advanced).mp4 123.3 MB
  • 21 - Effective Learning Strategies for Machine Learning FAQ/004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 113.4 MB
  • 09 - Spam Detection/006 Spam Detection in Python.mp4 112.8 MB
  • 07 - Cipher Decryption (Advanced)/004 Genetic Algorithms.mp4 110.3 MB
  • 03 - Vector Models and Text Preprocessing/010 Count Vectorizer (Code).mp4 106.9 MB
  • 06 - Article Spinner (Intermediate)/004 Article Spinner in Python (pt 1).mp4 100.6 MB
  • 16 - Feedforward Artificial Neural Networks/004 Activation Functions.mp4 93.7 MB
  • 17 - Convolutional Neural Networks/006 CNN Architecture.mp4 93.6 MB
  • 11 - Text Summarization/008 TextRank in Python (Advanced).mp4 86.3 MB
  • 18 - Recurrent Neural Networks/006 GRU and LSTM (pt 1).mp4 86.2 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/002 SVD (Singular Value Decomposition) Intuition.mp4 85.8 MB
  • 15 - The Neuron/004 Text Classification in Tensorflow.mp4 85.6 MB
  • 17 - Convolutional Neural Networks/002 What is Convolution.mp4 83.7 MB
  • 03 - Vector Models and Text Preprocessing/016 How to Build TF-IDF From Scratch.mp4 83.7 MB
  • 21 - Effective Learning Strategies for Machine Learning FAQ/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 83.5 MB
  • 11 - Text Summarization/004 Text Summarization in Python.mp4 81.9 MB
  • 06 - Article Spinner (Intermediate)/005 Article Spinner in Python (pt 2).mp4 79.0 MB
  • 17 - Convolutional Neural Networks/005 Convolution on Color Images.mp4 78.8 MB
  • 03 - Vector Models and Text Preprocessing/009 Stemming and Lemmatization Demo.mp4 78.5 MB
  • 03 - Vector Models and Text Preprocessing/006 Tokenization.mp4 77.1 MB
  • 01 - Introduction/001 Introduction and Outline.mp4 76.5 MB
  • 12 - Topic Modeling/006 Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4 75.9 MB
  • 05 - Markov Models (Intermediate)/008 Building a Text Classifier (Code pt 2).mp4 75.7 MB
  • 20 - Extra Help With Python Coding for Beginners FAQ/002 How to Code by Yourself (part 1).mp4 75.3 MB
  • 20 - Extra Help With Python Coding for Beginners FAQ/004 Proof that using Jupyter Notebook is the same as not using it.mp4 72.8 MB
  • 15 - The Neuron/002 Fitting a Line.mp4 71.9 MB
  • 03 - Vector Models and Text Preprocessing/018 Neural Word Embeddings Demo.mp4 70.1 MB
  • 07 - Cipher Decryption (Advanced)/003 Language Models (Review).mp4 68.7 MB
  • 02 - Getting Set Up/002 How to use Github & Extra Coding Tips (Optional).mp4 67.0 MB
  • 10 - Sentiment Analysis/002 Logistic Regression Intuition (pt 1).mp4 66.7 MB
  • 10 - Sentiment Analysis/006 Sentiment Analysis in Python (pt 1).mp4 66.2 MB
  • 05 - Markov Models (Intermediate)/011 Language Model (Code pt 1).mp4 65.9 MB
  • 09 - Spam Detection/004 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 63.1 MB
  • 12 - Topic Modeling/005 Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4 63.1 MB
  • 03 - Vector Models and Text Preprocessing/012 TF-IDF (Theory).mp4 61.4 MB
  • 03 - Vector Models and Text Preprocessing/008 Stemming and Lemmatization.mp4 60.7 MB
  • 05 - Markov Models (Intermediate)/007 Building a Text Classifier (Code pt 1).mp4 60.5 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/004 Latent Semantic Analysis Latent Semantic Indexing in Python.mp4 60.3 MB
  • 03 - Vector Models and Text Preprocessing/005 Count Vectorizer (Theory).mp4 60.2 MB
  • 18 - Recurrent Neural Networks/005 RNNs Paying Attention to Shapes.mp4 59.9 MB
  • 16 - Feedforward Artificial Neural Networks/003 The Geometrical Picture.mp4 59.3 MB
  • 03 - Vector Models and Text Preprocessing/021 How To Do NLP In Other Languages.mp4 58.7 MB
  • 12 - Topic Modeling/002 Latent Dirichlet Allocation (LDA) - Essentials.mp4 57.9 MB
  • 09 - Spam Detection/005 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 56.6 MB
  • 19 - Setting Up Your Environment FAQ/001 Anaconda Environment Setup.mp4 55.2 MB
  • 12 - Topic Modeling/007 Non-Negative Matrix Factorization (NMF) Intuition.mp4 55.0 MB
  • 05 - Markov Models (Intermediate)/012 Language Model (Code pt 2).mp4 55.0 MB
  • 10 - Sentiment Analysis/007 Sentiment Analysis in Python (pt 2).mp4 54.5 MB
  • 15 - The Neuron/006 How does a model learn.mp4 54.1 MB
  • 09 - Spam Detection/002 Naive Bayes Intuition.mp4 53.8 MB
  • 19 - Setting Up Your Environment FAQ/002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 53.4 MB
  • 18 - Recurrent Neural Networks/007 GRU and LSTM (pt 2).mp4 52.8 MB
  • 16 - Feedforward Artificial Neural Networks/008 Text Preprocessing Code Preparation.mp4 52.4 MB
  • 11 - Text Summarization/006 TextRank - How It Really Works (Advanced).mp4 51.7 MB
  • 20 - Extra Help With Python Coding for Beginners FAQ/003 How to Code by Yourself (part 2).mp4 51.5 MB
  • 03 - Vector Models and Text Preprocessing/003 What is a Vector.mp4 51.3 MB
  • 03 - Vector Models and Text Preprocessing/015 Word-to-Index Mapping.mp4 49.9 MB
  • 16 - Feedforward Artificial Neural Networks/002 Forward Propagation.mp4 49.0 MB
  • 11 - Text Summarization/005 TextRank Intuition.mp4 48.2 MB
  • 18 - Recurrent Neural Networks/008 RNN for Text Classification in Tensorflow.mp4 48.1 MB
  • 05 - Markov Models (Intermediate)/003 The Markov Model.mp4 48.1 MB
  • 03 - Vector Models and Text Preprocessing/017 Neural Word Embeddings.mp4 47.8 MB
  • 15 - The Neuron/005 The Neuron.mp4 47.4 MB
  • 11 - Text Summarization/009 Text Summarization in Python - The Easy Way (Beginner).mp4 47.4 MB
  • 03 - Vector Models and Text Preprocessing/011 Vector Similarity.mp4 47.3 MB
  • 05 - Markov Models (Intermediate)/009 Language Model (Theory).mp4 47.1 MB
  • 16 - Feedforward Artificial Neural Networks/005 Multiclass Classification.mp4 46.6 MB
  • 02 - Getting Set Up/001 Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 45.7 MB
  • 10 - Sentiment Analysis/001 Sentiment Analysis - Problem Description.mp4 44.8 MB
  • 16 - Feedforward Artificial Neural Networks/010 Embeddings.mp4 44.3 MB
  • 18 - Recurrent Neural Networks/004 RNN Code Preparation.mp4 44.2 MB
  • 17 - Convolutional Neural Networks/008 Convolutional Neural Network for NLP in Tensorflow.mp4 44.1 MB
  • 06 - Article Spinner (Intermediate)/001 Article Spinning - Problem Description.mp4 44.0 MB
  • 18 - Recurrent Neural Networks/003 Simple RNN Elman Unit (pt 2).mp4 43.2 MB
  • 07 - Cipher Decryption (Advanced)/010 Code pt 5.mp4 42.9 MB
  • 18 - Recurrent Neural Networks/002 Simple RNN Elman Unit (pt 1).mp4 42.8 MB
  • 17 - Convolutional Neural Networks/007 CNNs for Text.mp4 42.4 MB
  • 22 - Appendix FAQ Finale/002 BONUS.mp4 41.8 MB
  • 10 - Sentiment Analysis/004 Logistic Regression Training and Interpretation (pt 3).mp4 41.6 MB
  • 07 - Cipher Decryption (Advanced)/011 Code pt 6.mp4 41.3 MB
  • 07 - Cipher Decryption (Advanced)/007 Code pt 2.mp4 41.0 MB
  • 21 - Effective Learning Strategies for Machine Learning FAQ/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
  • 16 - Feedforward Artificial Neural Networks/001 ANN - Section Introduction.mp4 40.5 MB
  • 16 - Feedforward Artificial Neural Networks/015 Aside How to Choose Hyperparameters (Optional).mp4 39.9 MB
  • 16 - Feedforward Artificial Neural Networks/007 Text Classification ANN in Tensorflow.mp4 37.9 MB
  • 12 - Topic Modeling/008 Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp4 37.8 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/003 LSA LSI Applying SVD to NLP.mp4 36.1 MB
  • 05 - Markov Models (Intermediate)/004 Probability Smoothing and Log-Probabilities.mp4 35.7 MB
  • 15 - The Neuron/003 Classification Code Preparation.mp4 34.5 MB
  • 05 - Markov Models (Intermediate)/002 The Markov Property.mp4 33.8 MB
  • 18 - Recurrent Neural Networks/010 Named Entity Recognition (NER) in Tensorflow.mp4 33.1 MB
  • 09 - Spam Detection/001 Spam Detection - Problem Description.mp4 32.9 MB
  • 16 - Feedforward Artificial Neural Networks/009 Text Preprocessing in Tensorflow.mp4 32.4 MB
  • 08 - Machine Learning Models (Introduction)/001 Machine Learning Models (Introduction).mp4 31.0 MB
  • 07 - Cipher Decryption (Advanced)/008 Code pt 3.mp4 31.0 MB
  • 05 - Markov Models (Intermediate)/006 Building a Text Classifier (Exercise Prompt).mp4 30.8 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/005 LSA LSI Exercises.mp4 30.5 MB
  • 05 - Markov Models (Intermediate)/005 Building a Text Classifier (Theory).mp4 30.3 MB
  • 17 - Convolutional Neural Networks/004 What is Convolution (Weight Sharing).mp4 30.2 MB
  • 05 - Markov Models (Intermediate)/010 Language Model (Exercise Prompt).mp4 30.2 MB
  • 03 - Vector Models and Text Preprocessing/002 Basic Definitions for NLP.mp4 29.7 MB
  • 06 - Article Spinner (Intermediate)/006 Case Study Article Spinning Gone Wrong.mp4 29.6 MB
  • 03 - Vector Models and Text Preprocessing/022 Suggestion Box.mp4 28.5 MB
  • 04 - Probabilistic Models (Introduction)/001 Probabilistic Models (Introduction).mp4 28.2 MB
  • 01 - Introduction/002 Are You Beginner, Intermediate, or Advanced All are OK!.mp4 28.0 MB
  • 07 - Cipher Decryption (Advanced)/001 Section Introduction.mp4 27.6 MB
  • 11 - Text Summarization/002 Text Summarization Using Vectors.mp4 27.0 MB
  • 11 - Text Summarization/001 Text Summarization Section Introduction.mp4 27.0 MB
  • 07 - Cipher Decryption (Advanced)/009 Code pt 4.mp4 26.9 MB
  • 17 - Convolutional Neural Networks/001 CNN - Section Introduction.mp4 26.9 MB
  • 06 - Article Spinner (Intermediate)/003 Article Spinner Exercise Prompt.mp4 25.8 MB
  • 17 - Convolutional Neural Networks/003 What is Convolution (Pattern Matching).mp4 25.8 MB
  • 14 - Deep Learning (Introduction)/001 Deep Learning Introduction (Intermediate-Advanced).mp4 25.7 MB
  • 07 - Cipher Decryption (Advanced)/013 Section Conclusion.mp4 25.4 MB
  • 10 - Sentiment Analysis/003 Multiclass Logistic Regression (pt 2).mp4 24.8 MB
  • 03 - Vector Models and Text Preprocessing/007 Stopwords.mp4 24.6 MB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/001 LSA LSI Section Introduction.mp4 22.0 MB
  • 18 - Recurrent Neural Networks/001 RNN - Section Introduction.mp4 21.9 MB
  • 03 - Vector Models and Text Preprocessing/019 Vector Models & Text Preprocessing Summary.mp4 21.9 MB
  • 07 - Cipher Decryption (Advanced)/005 Code Preparation.mp4 21.6 MB
  • 16 - Feedforward Artificial Neural Networks/006 ANN Code Preparation.mp4 21.1 MB
  • 11 - Text Summarization/010 Text Summarization Section Summary.mp4 21.1 MB
  • 21 - Effective Learning Strategies for Machine Learning FAQ/001 How to Succeed in this Course (Long Version).mp4 18.7 MB
  • 20 - Extra Help With Python Coding for Beginners FAQ/001 Where to get the code, notebooks, and data.mp4 18.6 MB
  • 03 - Vector Models and Text Preprocessing/001 Vector Models & Text Preprocessing Intro.mp4 18.4 MB
  • 07 - Cipher Decryption (Advanced)/002 Ciphers.mp4 18.0 MB
  • 12 - Topic Modeling/001 Topic Modeling Section Introduction.mp4 17.9 MB
  • 10 - Sentiment Analysis/005 Sentiment Analysis - Exercise Prompt.mp4 17.4 MB
  • 22 - Appendix FAQ Finale/001 What is the Appendix.mp4 17.2 MB
  • 07 - Cipher Decryption (Advanced)/006 Code pt 1.mp4 16.8 MB
  • 06 - Article Spinner (Intermediate)/002 Article Spinning - N-Gram Approach.mp4 16.7 MB
  • 16 - Feedforward Artificial Neural Networks/011 CBOW (Advanced).mp4 16.5 MB
  • 05 - Markov Models (Intermediate)/013 Markov Models Section Summary.mp4 16.3 MB
  • 07 - Cipher Decryption (Advanced)/012 Cipher Decryption - Additional Discussion.mp4 15.4 MB
  • 18 - Recurrent Neural Networks/011 Exercise Return to CNNs (Advanced).mp4 15.3 MB
  • 12 - Topic Modeling/003 LDA - Code Preparation.mp4 15.2 MB
  • 03 - Vector Models and Text Preprocessing/004 Bag of Words.mp4 14.5 MB
  • 03 - Vector Models and Text Preprocessing/013 (Interactive) Recommender Exercise Prompt.mp4 14.0 MB
  • 05 - Markov Models (Intermediate)/001 Markov Models Section Introduction.mp4 13.7 MB
  • 15 - The Neuron/001 The Neuron - Section Introduction.mp4 11.5 MB
  • 15 - The Neuron/007 The Neuron - Section Summary.mp4 10.8 MB
  • 12 - Topic Modeling/009 Topic Modeling Section Summary.mp4 10.3 MB
  • 18 - Recurrent Neural Networks/012 RNN - Section Summary.mp4 9.5 MB
  • 12 - Topic Modeling/004 LDA - Maybe Useful Picture (Optional).mp4 9.4 MB
  • 09 - Spam Detection/003 Spam Detection - Exercise Prompt.mp4 9.2 MB
  • 17 - Convolutional Neural Networks/009 CNN - Section Summary.mp4 8.6 MB
  • 11 - Text Summarization/003 Text Summarization Exercise Prompt.mp4 8.5 MB
  • 16 - Feedforward Artificial Neural Networks/014 ANN - Section Summary.mp4 8.0 MB
  • 11 - Text Summarization/007 TextRank Exercise Prompt (Advanced).mp4 7.8 MB
  • 03 - Vector Models and Text Preprocessing/020 Text Summarization Preview.mp4 6.6 MB
  • 16 - Feedforward Artificial Neural Networks/012 CBOW Exercise Prompt.mp4 5.3 MB
  • 21 - Effective Learning Strategies for Machine Learning FAQ/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced_en.srt 33.2 kB
  • 07 - Cipher Decryption (Advanced)/004 Genetic Algorithms_en.srt 29.9 kB
  • 17 - Convolutional Neural Networks/006 CNN Architecture_en.srt 29.4 kB
  • 03 - Vector Models and Text Preprocessing/014 TF-IDF (Code)_en.srt 25.4 kB
  • 21 - Effective Learning Strategies for Machine Learning FAQ/004 Machine Learning and AI Prerequisite Roadmap (pt 2)_en.srt 24.2 kB
  • 18 - Recurrent Neural Networks/006 GRU and LSTM (pt 1)_en.srt 23.8 kB
  • 16 - Feedforward Artificial Neural Networks/004 Activation Functions_en.srt 23.5 kB
  • 20 - Extra Help With Python Coding for Beginners FAQ/002 How to Code by Yourself (part 1)_en.srt 23.2 kB
  • 18 - Recurrent Neural Networks/009 Parts-of-Speech (POS) Tagging in Tensorflow_en.srt 23.2 kB
  • 10 - Sentiment Analysis/002 Logistic Regression Intuition (pt 1)_en.srt 23.1 kB
  • 17 - Convolutional Neural Networks/005 Convolution on Color Images_en.srt 21.4 kB
  • 06 - Article Spinner (Intermediate)/004 Article Spinner in Python (pt 1)_en.srt 21.2 kB
  • 17 - Convolutional Neural Networks/002 What is Convolution_en.srt 21.2 kB
  • 07 - Cipher Decryption (Advanced)/003 Language Models (Review)_en.srt 21.0 kB
  • 16 - Feedforward Artificial Neural Networks/013 CBOW in Tensorflow (Advanced)_en.srt 20.8 kB
  • 12 - Topic Modeling/005 Latent Dirichlet Allocation (LDA) - Intuition (Advanced)_en.srt 20.7 kB
  • 19 - Setting Up Your Environment FAQ/001 Anaconda Environment Setup_en.srt 20.6 kB
  • 03 - Vector Models and Text Preprocessing/006 Tokenization_en.srt 20.3 kB
  • 09 - Spam Detection/006 Spam Detection in Python_en.srt 19.7 kB
  • 03 - Vector Models and Text Preprocessing/005 Count Vectorizer (Theory)_en.srt 19.6 kB
  • 03 - Vector Models and Text Preprocessing/010 Count Vectorizer (Code)_en.srt 19.6 kB
  • 03 - Vector Models and Text Preprocessing/016 How to Build TF-IDF From Scratch_en.srt 19.0 kB
  • 15 - The Neuron/002 Fitting a Line_en.srt 18.8 kB
  • 03 - Vector Models and Text Preprocessing/012 TF-IDF (Theory)_en.srt 18.7 kB
  • 11 - Text Summarization/008 TextRank in Python (Advanced)_en.srt 17.5 kB
  • 09 - Spam Detection/004 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1)_en.srt 17.2 kB
  • 21 - Effective Learning Strategies for Machine Learning FAQ/003 Machine Learning and AI Prerequisite Roadmap (pt 1)_en.srt 17.0 kB
  • 05 - Markov Models (Intermediate)/003 The Markov Model_en.srt 16.9 kB
  • 03 - Vector Models and Text Preprocessing/008 Stemming and Lemmatization_en.srt 16.2 kB
  • 02 - Getting Set Up/002 How to use Github & Extra Coding Tips (Optional)_en.srt 16.1 kB
  • 01 - Introduction/001 Introduction and Outline_en.srt 15.8 kB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/002 SVD (Singular Value Decomposition) Intuition_en.srt 15.8 kB
  • 09 - Spam Detection/002 Naive Bayes Intuition_en.srt 15.6 kB
  • 12 - Topic Modeling/002 Latent Dirichlet Allocation (LDA) - Essentials_en.srt 15.5 kB
  • 03 - Vector Models and Text Preprocessing/011 Vector Similarity_en.srt 15.5 kB
  • 18 - Recurrent Neural Networks/007 GRU and LSTM (pt 2)_en.srt 15.5 kB
  • 11 - Text Summarization/004 Text Summarization in Python_en.srt 15.4 kB
  • 16 - Feedforward Artificial Neural Networks/008 Text Preprocessing Code Preparation_en.srt 15.2 kB
  • 03 - Vector Models and Text Preprocessing/003 What is a Vector_en.srt 15.2 kB
  • 03 - Vector Models and Text Preprocessing/015 Word-to-Index Mapping_en.srt 15.2 kB
  • 19 - Setting Up Your Environment FAQ/002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow_en.srt 15.0 kB
  • 03 - Vector Models and Text Preprocessing/021 How To Do NLP In Other Languages_en.srt 14.9 kB
  • 21 - Effective Learning Strategies for Machine Learning FAQ/001 How to Succeed in this Course (Long Version)_en.srt 14.9 kB
  • 09 - Spam Detection/005 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2)_en.srt 14.8 kB
  • 15 - The Neuron/006 How does a model learn_en.srt 14.7 kB
  • 20 - Extra Help With Python Coding for Beginners FAQ/004 Proof that using Jupyter Notebook is the same as not using it_en.srt 14.7 kB
  • 03 - Vector Models and Text Preprocessing/009 Stemming and Lemmatization Demo_en.srt 14.2 kB
  • 05 - Markov Models (Intermediate)/008 Building a Text Classifier (Code pt 2)_en.srt 14.1 kB
  • 12 - Topic Modeling/007 Non-Negative Matrix Factorization (NMF) Intuition_en.srt 14.1 kB
  • 11 - Text Summarization/006 TextRank - How It Really Works (Advanced)_en.srt 13.8 kB
  • 03 - Vector Models and Text Preprocessing/017 Neural Word Embeddings_en.srt 13.8 kB
  • 20 - Extra Help With Python Coding for Beginners FAQ/003 How to Code by Yourself (part 2)_en.srt 13.6 kB
  • 05 - Markov Models (Intermediate)/009 Language Model (Theory)_en.srt 13.6 kB
  • 12 - Topic Modeling/006 Topic Modeling with Latent Dirichlet Allocation (LDA) in Python_en.srt 13.6 kB
  • 05 - Markov Models (Intermediate)/011 Language Model (Code pt 1)_en.srt 13.5 kB
  • 18 - Recurrent Neural Networks/003 Simple RNN Elman Unit (pt 2)_en.srt 13.2 kB
  • 03 - Vector Models and Text Preprocessing/018 Neural Word Embeddings Demo_en.srt 13.0 kB
  • 15 - The Neuron/005 The Neuron_en.srt 13.0 kB
  • 16 - Feedforward Artificial Neural Networks/010 Embeddings_en.srt 12.9 kB
  • 16 - Feedforward Artificial Neural Networks/002 Forward Propagation_en.srt 12.9 kB
  • 18 - Recurrent Neural Networks/004 RNN Code Preparation_en.srt 12.9 kB
  • 06 - Article Spinner (Intermediate)/005 Article Spinner in Python (pt 2)_en.srt 12.7 kB
  • 02 - Getting Set Up/001 Get Your Hands Dirty, Practical Coding Experience, Data Links_en.srt 12.3 kB
  • 05 - Markov Models (Intermediate)/007 Building a Text Classifier (Code pt 1)_en.srt 12.1 kB
  • 16 - Feedforward Artificial Neural Networks/003 The Geometrical Picture_en.srt 12.1 kB
  • 15 - The Neuron/004 Text Classification in Tensorflow_en.srt 12.0 kB
  • 10 - Sentiment Analysis/006 Sentiment Analysis in Python (pt 1)_en.srt 11.9 kB
  • 18 - Recurrent Neural Networks/002 Simple RNN Elman Unit (pt 1)_en.srt 11.8 kB
  • 16 - Feedforward Artificial Neural Networks/005 Multiclass Classification_en.srt 11.6 kB
  • 05 - Markov Models (Intermediate)/012 Language Model (Code pt 2)_en.srt 11.6 kB
  • 11 - Text Summarization/005 TextRank Intuition_en.srt 11.2 kB
  • 10 - Sentiment Analysis/004 Logistic Regression Training and Interpretation (pt 3)_en.srt 11.1 kB
  • 06 - Article Spinner (Intermediate)/001 Article Spinning - Problem Description_en.srt 11.0 kB
  • 05 - Markov Models (Intermediate)/004 Probability Smoothing and Log-Probabilities_en.srt 10.5 kB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/003 LSA LSI Applying SVD to NLP_en.srt 10.5 kB
  • 18 - Recurrent Neural Networks/005 RNNs Paying Attention to Shapes_en.srt 10.4 kB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/004 Latent Semantic Analysis Latent Semantic Indexing in Python_en.srt 10.3 kB
  • 10 - Sentiment Analysis/001 Sentiment Analysis - Problem Description_en.srt 10.1 kB
  • 17 - Convolutional Neural Networks/007 CNNs for Text_en.srt 10.0 kB
  • 10 - Sentiment Analysis/007 Sentiment Analysis in Python (pt 2)_en.srt 10.0 kB
  • 15 - The Neuron/003 Classification Code Preparation_en.srt 9.7 kB
  • 05 - Markov Models (Intermediate)/002 The Markov Property_en.srt 9.7 kB
  • 05 - Markov Models (Intermediate)/005 Building a Text Classifier (Theory)_en.srt 9.7 kB
  • 16 - Feedforward Artificial Neural Networks/001 ANN - Section Introduction_en.srt 9.5 kB
  • 07 - Cipher Decryption (Advanced)/007 Code pt 2_en.srt 9.5 kB
  • 05 - Markov Models (Intermediate)/010 Language Model (Exercise Prompt)_en.srt 9.2 kB
  • 07 - Cipher Decryption (Advanced)/010 Code pt 5_en.srt 9.0 kB
  • 05 - Markov Models (Intermediate)/006 Building a Text Classifier (Exercise Prompt)_en.srt 9.0 kB
  • 09 - Spam Detection/001 Spam Detection - Problem Description_en.srt 8.9 kB
  • 16 - Feedforward Artificial Neural Networks/015 Aside How to Choose Hyperparameters (Optional)_en.srt 8.8 kB
  • 10 - Sentiment Analysis/003 Multiclass Logistic Regression (pt 2)_en.srt 8.7 kB
  • 07 - Cipher Decryption (Advanced)/013 Section Conclusion_en.srt 8.5 kB
  • 17 - Convolutional Neural Networks/004 What is Convolution (Weight Sharing)_en.srt 8.2 kB
  • 22 - Appendix FAQ Finale/002 BONUS_en.srt 8.1 kB
  • 08 - Machine Learning Models (Introduction)/001 Machine Learning Models (Introduction)_en.srt 8.0 kB
  • 11 - Text Summarization/009 Text Summarization in Python - The Easy Way (Beginner)_en.srt 8.0 kB
  • 06 - Article Spinner (Intermediate)/003 Article Spinner Exercise Prompt_en.srt 7.8 kB
  • 06 - Article Spinner (Intermediate)/006 Case Study Article Spinning Gone Wrong_en.srt 7.7 kB
  • 11 - Text Summarization/001 Text Summarization Section Introduction_en.srt 7.7 kB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/005 LSA LSI Exercises_en.srt 7.5 kB
  • 11 - Text Summarization/002 Text Summarization Using Vectors_en.srt 7.5 kB
  • 07 - Cipher Decryption (Advanced)/011 Code pt 6_en.srt 7.4 kB
  • 01 - Introduction/002 Are You Beginner, Intermediate, or Advanced All are OK!_en.srt 7.4 kB
  • 17 - Convolutional Neural Networks/003 What is Convolution (Pattern Matching)_en.srt 7.1 kB
  • 14 - Deep Learning (Introduction)/001 Deep Learning Introduction (Intermediate-Advanced)_en.srt 6.9 kB
  • 07 - Cipher Decryption (Advanced)/005 Code Preparation_en.srt 6.9 kB
  • 07 - Cipher Decryption (Advanced)/001 Section Introduction_en.srt 6.8 kB
  • 03 - Vector Models and Text Preprocessing/002 Basic Definitions for NLP_en.srt 6.8 kB
  • 18 - Recurrent Neural Networks/001 RNN - Section Introduction_en.srt 6.5 kB
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  • 16 - Feedforward Artificial Neural Networks/009 Text Preprocessing in Tensorflow_en.srt 6.5 kB
  • 04 - Probabilistic Models (Introduction)/001 Probabilistic Models (Introduction)_en.srt 6.4 kB
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  • 18 - Recurrent Neural Networks/010 Named Entity Recognition (NER) in Tensorflow_en.srt 6.3 kB
  • 16 - Feedforward Artificial Neural Networks/006 ANN Code Preparation_en.srt 6.1 kB
  • 17 - Convolutional Neural Networks/001 CNN - Section Introduction_en.srt 6.1 kB
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  • 16 - Feedforward Artificial Neural Networks/011 CBOW (Advanced)_en.srt 5.4 kB
  • 06 - Article Spinner (Intermediate)/002 Article Spinning - N-Gram Approach_en.srt 5.3 kB
  • 13 - Latent Semantic Analysis (Latent Semantic Indexing)/001 LSA LSI Section Introduction_en.srt 5.3 kB
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  • 17 - Convolutional Neural Networks/008 Convolutional Neural Network for NLP in Tensorflow_en.srt 5.2 kB
  • 16 - Feedforward Artificial Neural Networks/007 Text Classification ANN in Tensorflow_en.srt 5.1 kB
  • 03 - Vector Models and Text Preprocessing/001 Vector Models & Text Preprocessing Intro_en.srt 5.1 kB
  • 12 - Topic Modeling/003 LDA - Code Preparation_en.srt 5.0 kB
  • 12 - Topic Modeling/008 Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python_en.srt 5.0 kB
  • 07 - Cipher Decryption (Advanced)/009 Code pt 4_en.srt 5.0 kB
  • 07 - Cipher Decryption (Advanced)/002 Ciphers_en.srt 4.9 kB
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  • 11 - Text Summarization/010 Text Summarization Section Summary_en.srt 4.5 kB
  • 20 - Extra Help With Python Coding for Beginners FAQ/001 Where to get the code, notebooks, and data_en.srt 4.4 kB
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  • 03 - Vector Models and Text Preprocessing/004 Bag of Words_en.srt 3.2 kB
  • 15 - The Neuron/001 The Neuron - Section Introduction_en.srt 3.0 kB
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  • 18 - Recurrent Neural Networks/012 RNN - Section Summary_en.srt 2.4 kB
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  • 11 - Text Summarization/007 TextRank Exercise Prompt (Advanced)_en.srt 1.8 kB
  • 03 - Vector Models and Text Preprocessing/020 Text Summarization Preview_en.srt 1.7 kB
  • 17 - Convolutional Neural Networks/009 CNN - Section Summary_en.srt 1.7 kB
  • 16 - Feedforward Artificial Neural Networks/012 CBOW Exercise Prompt_en.srt 972 Bytes
  • 20 - Extra Help With Python Coding for Beginners FAQ/external-links.txt 298 Bytes
  • 02 - Getting Set Up/external-links.txt 215 Bytes
  • 0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • [CourseClub.Me].url 122 Bytes
  • 02 - Getting Set Up/001 Data-Links.url 120 Bytes
  • 20 - Extra Help With Python Coding for Beginners FAQ/001 Data-Links.url 120 Bytes
  • 02 - Getting Set Up/001 Github-Link.url 102 Bytes
  • 20 - Extra Help With Python Coding for Beginners FAQ/001 Github-Link.url 102 Bytes
  • 20 - Extra Help With Python Coding for Beginners FAQ/001 Code-Link.url 88 Bytes
  • 0. Websites you may like/[GigaCourse.Com].url 49 Bytes
  • [GigaCourse.Com].url 49 Bytes

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