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[DesireCourse.Net] Udemy - Natural Language Processing with Deep Learning in Python

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Description
Natural Language Processing with Deep Learning in Python

Complete guide on deriving and implementing word2vec, GLoVe, word embeddings, and sentiment analysis with recursive nets

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File list
  • [DesireCourse.Net] Udemy - Natural Language Processing with Deep Learning in Python
  • 1. Outline, Review, and Logistical Things/1. Introduction, Outline, and Review.mp4 37.1 MB
  • 1. Outline, Review, and Logistical Things/1. Introduction, Outline, and Review.srt 8.7 KB
  • 1. Outline, Review, and Logistical Things/2. How to Succeed in this Course.mp4 3.3 MB
  • 1. Outline, Review, and Logistical Things/2. How to Succeed in this Course.srt 4 KB
  • 1. Outline, Review, and Logistical Things/3. Tensorflow or Theano - Your Choice!.mp4 18.6 MB
  • 1. Outline, Review, and Logistical Things/3. Tensorflow or Theano - Your Choice!.srt 5.4 KB
  • 1. Outline, Review, and Logistical Things/4. Where to get the code data for this course.mp4 6.5 MB
  • 1. Outline, Review, and Logistical Things/4. Where to get the code data for this course.srt 2.2 KB
  • 1. Outline, Review, and Logistical Things/5. Preprocessed Wikipedia Data.mp4 21.6 MB
  • 1. Outline, Review, and Logistical Things/5. Preprocessed Wikipedia Data.srt 3.8 KB
  • 10. Legacy Word2vec Lectures/1. (Legacy) What is a word embedding.mp4 18 MB
  • 10. Legacy Word2vec Lectures/1. (Legacy) What is a word embedding.srt 13.8 KB
  • 10. Legacy Word2vec Lectures/2. (Legacy) Using pre-trained word embeddings.mp4 4.1 MB
  • 10. Legacy Word2vec Lectures/2. (Legacy) Using pre-trained word embeddings.srt 3.1 KB
  • 10. Legacy Word2vec Lectures/3. (Legacy) Word analogies using word embeddings.mp4 6.6 MB
  • 10. Legacy Word2vec Lectures/3. (Legacy) Word analogies using word embeddings.srt 5.5 KB
  • 10. Legacy Word2vec Lectures/4. (Legacy) TF-IDF and t-SNE experiment.mp4 26.7 MB
  • 10. Legacy Word2vec Lectures/4. (Legacy) TF-IDF and t-SNE experiment.srt 12.9 KB
  • 10. Legacy Word2vec Lectures/5. (Legacy) Word2Vec introduction.mp4 8.8 MB
  • 10. Legacy Word2vec Lectures/5. (Legacy) Word2Vec introduction.srt 6.8 KB
  • 11. Appendix FAQ/1. What is the Appendix.mp4 5.5 MB
  • 11. Appendix FAQ/1. What is the Appendix.srt 3.7 KB
  • 11. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.mp4 78.3 MB
  • 11. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.srt 14.1 KB
  • 11. Appendix FAQ/11. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 37.8 MB
  • 11. Appendix FAQ/11. BONUS Where to get Udemy coupons and FREE deep learning material.srt 7.9 KB
  • 11. Appendix FAQ/12. Python 2 vs Python 3.mp4 7.8 MB
  • 11. Appendix FAQ/12. Python 2 vs Python 3.srt 6.1 KB
  • 11. Appendix FAQ/13. Is Theano Dead.mp4 17.8 MB
  • 11. Appendix FAQ/13. Is Theano Dead.srt 12.9 KB
  • 11. Appendix FAQ/14. What order should I take your courses in (part 1).mp4 29.3 MB
  • 11. Appendix FAQ/14. What order should I take your courses in (part 1).srt 16 KB
  • 11. Appendix FAQ/15. What order should I take your courses in (part 2).mp4 37.6 MB
  • 11. Appendix FAQ/15. What order should I take your courses in (part 2).srt 23 KB
  • 11. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.mp4 3.8 MB
  • 11. Appendix FAQ/2. How to install wp2txt or WikiExtractor.py.srt 3.3 KB
  • 11. Appendix FAQ/3. How to Uncompress a .tar.gz file.mp4 12.9 MB
  • 11. Appendix FAQ/3. How to Uncompress a .tar.gz file.srt 4.1 KB
  • 11. Appendix FAQ/4. Windows-Focused Environment Setup 2018.mp4 186.4 MB
  • 11. Appendix FAQ/4. Windows-Focused Environment Setup 2018.srt 20.1 KB
  • 11. Appendix FAQ/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.9 MB
  • 11. Appendix FAQ/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.5 KB
  • 11. Appendix FAQ/6. How to Code by Yourself (part 1).mp4 24.5 MB
  • 11. Appendix FAQ/6. How to Code by Yourself (part 1).srt 22.8 KB
  • 11. Appendix FAQ/7. How to Code by Yourself (part 2).mp4 14.8 MB
  • 11. Appendix FAQ/7. How to Code by Yourself (part 2).srt 13.3 KB
  • 11. Appendix FAQ/8. How to Succeed in this Course (Long Version).mp4 13 MB
  • 11. Appendix FAQ/8. How to Succeed in this Course (Long Version).srt 14.7 KB
  • 11. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39 MB
  • 11. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 31.8 KB
  • 2. Beginner's Corner Working with Word Vectors/1. What are vectors.mp4 35.3 MB
  • 2. Beginner's Corner Working with Word Vectors/1. What are vectors.srt 10.3 KB
  • 2. Beginner's Corner Working with Word Vectors/2. What is a word analogy.mp4 31.2 MB
  • 2. Beginner's Corner Working with Word Vectors/2. What is a word analogy.srt 10.3 KB
  • 2. Beginner's Corner Working with Word Vectors/3. Trying to find and assess word vectors using TF-IDF and t-SNE.mp4 32.1 MB
  • 2. Beginner's Corner Working with Word Vectors/3. Trying to find and assess word vectors using TF-IDF and t-SNE.srt 8.4 KB
  • 2. Beginner's Corner Working with Word Vectors/4. Pretrained word vectors from GloVe.mp4 97.5 MB
  • 2. Beginner's Corner Working with Word Vectors/4. Pretrained word vectors from GloVe.srt 14.2 KB
  • 2. Beginner's Corner Working with Word Vectors/5. Pretrained word vectors from word2vec.mp4 63.2 MB
  • 2. Beginner's Corner Working with Word Vectors/5. Pretrained word vectors from word2vec.srt 8.1 KB
  • 2. Beginner's Corner Working with Word Vectors/6. Text Classification with word vectors.mp4 20.6 MB
  • 2. Beginner's Corner Working with Word Vectors/6. Text Classification with word vectors.srt 5.5 KB
  • 2. Beginner's Corner Working with Word Vectors/7. Text Classification in Code.mp4 54.6 MB
  • 2. Beginner's Corner Working with Word Vectors/7. Text Classification in Code.srt 7.3 KB
  • 2. Beginner's Corner Working with Word Vectors/8. Using pretrained vectors later in the course.mp4 13.9 MB
  • 2. Beginner's Corner Working with Word Vectors/8. Using pretrained vectors later in the course.srt 4.3 KB
  • 3. Review of Language Modeling and Neural Networks/1. Review Section Intro.mp4 5.5 MB
  • 3. Review of Language Modeling and Neural Networks/1. Review Section Intro.srt 4.3 KB
  • 3. Review of Language Modeling and Neural Networks/10. Review Section Summary.mp4 3 MB
  • 3. Review of Language Modeling and Neural Networks/10. Review Section Summary.srt 4.3 KB
  • 3. Review of Language Modeling and Neural Networks/2. Bigrams and Language Models.mp4 12.2 MB
  • 3. Review of Language Modeling and Neural Networks/2. Bigrams and Language Models.srt 17.2 KB
  • 3. Review of Language Modeling and Neural Networks/3. Bigrams in Code.mp4 17.9 MB
  • 3. Review of Language Modeling and Neural Networks/3. Bigrams in Code.srt 17.4 KB
  • 3. Review of Language Modeling and Neural Networks/4. Neural Bigram Model.mp4 39.7 MB
  • 3. Review of Language Modeling and Neural Networks/4. Neural Bigram Model.srt 9.7 KB
  • 3. Review of Language Modeling and Neural Networks/5. Neural Bigram Model in Code.mp4 8.3 MB
  • 3. Review of Language Modeling and Neural Networks/5. Neural Bigram Model in Code.srt 7.9 KB
  • 3. Review of Language Modeling and Neural Networks/6. Neural Network Bigram Model.mp4 8 MB
  • 3. Review of Language Modeling and Neural Networks/6. Neural Network Bigram Model.srt 11.3 KB
  • 3. Review of Language Modeling and Neural Networks/7. Neural Network Bigram Model in Code.mp4 5.2 MB
  • 3. Review of Language Modeling and Neural Networks/7. Neural Network Bigram Model in Code.srt 4 KB
  • 3. Review of Language Modeling and Neural Networks/8. Improving Efficiency.mp4 11.9 MB
  • 3. Review of Language Modeling and Neural Networks/8. Improving Efficiency.srt 17.6 KB
  • 3. Review of Language Modeling and Neural Networks/9. Improving Efficiency in Code.mp4 6.7 MB
  • 3. Review of Language Modeling and Neural Networks/9. Improving Efficiency in Code.srt 5.7 KB
  • 4. Word Embeddings and Word2Vec/1. Return of the Bigram.mp4 11.5 MB
  • 4. Word Embeddings and Word2Vec/1. Return of the Bigram.srt 3.8 KB
  • 4. Word Embeddings and Word2Vec/10. Word2Vec in Code with Numpy.mp4 108.2 MB
  • 4. Word Embeddings and Word2Vec/10. Word2Vec in Code with Numpy.srt 11.6 KB
  • 4. Word Embeddings and Word2Vec/11. Word2Vec Tensorflow Implementation Details.mp4 12.8 MB
  • 4. Word Embeddings and Word2Vec/11. Word2Vec Tensorflow Implementation Details.srt 5 KB
  • 4. Word Embeddings and Word2Vec/12. Word2Vec Tensorflow in Code.mp4 44.2 MB
  • 4. Word Embeddings and Word2Vec/12. Word2Vec Tensorflow in Code.srt 3.6 KB
  • 4. Word Embeddings and Word2Vec/13. How to update only part of a Theano shared variable.mp4 9.2 MB
  • 4. Word Embeddings and Word2Vec/13. How to update only part of a Theano shared variable.srt 7.7 KB
  • 4. Word Embeddings and Word2Vec/14. Word2Vec in Code with Theano.mp4 31 MB
  • 4. Word Embeddings and Word2Vec/14. Word2Vec in Code with Theano.srt 7.2 KB
  • 4. Word Embeddings and Word2Vec/15. Alternative to Wikipedia Data Brown Corpus.mp4 12.5 MB

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