种子简介

种子名称： [FreeCourseLab.com] Udemy - Natural Language Processing with Deep Learning in Python
文件类型： 视频
文件数目： 100个文件
文件大小： 3.12 GB
收录时间： 2023-2-14 18:32
已经下载： 3次
资源热度： 227
最近下载： 2024-11-25 07:29

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:7702ef015853f45369b4ef15363d46bd31826a11&dn=[FreeCourseLab.com] Udemy - Natural Language Processing with Deep Learning in Python 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

[FreeCourseLab.com] Udemy - Natural Language Processing with Deep Learning in Python.torrent

1. Outline, Review, and Logistical Things/1. Introduction, Outline, and Review.mp437.13MB

1. Outline, Review, and Logistical Things/2. Where to get the code data for this course.mp46.5MB

1. Outline, Review, and Logistical Things/3. How to Succeed in this Course.mp43.3MB

1. Outline, Review, and Logistical Things/4. Tensorflow or Theano - Your Choice!.mp418.58MB

10. Legacy Word2vec Lectures/1. (Legacy) What is a word embedding.mp418MB

10. Legacy Word2vec Lectures/2. (Legacy) Using pre-trained word embeddings.mp44.05MB

10. Legacy Word2vec Lectures/3. (Legacy) Word analogies using word embeddings.mp46.61MB

10. Legacy Word2vec Lectures/4. (Legacy) TF-IDF and t-SNE experiment.mp426.76MB

10. Legacy Word2vec Lectures/5. (Legacy) Word2Vec introduction.mp48.82MB

11. Appendix/1. What is the Appendix.mp45.45MB

11. Appendix/10. BONUS Where to get Udemy coupons and FREE deep learning material.mp44.02MB

11. Appendix/11. Python 2 vs Python 3.mp47.84MB

11. Appendix/12. Is Theano Dead.mp417.81MB

11. Appendix/13. What order should I take your courses in (part 1).mp429.33MB

11. Appendix/14. What order should I take your courses in (part 2).mp437.62MB

11. Appendix/2. How to install wp2txt or WikiExtractor.py.mp43.77MB

11. Appendix/3. Windows-Focused Environment Setup 2018.mp4186.39MB

11. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB

11. Appendix/5. How to Code by Yourself (part 1).mp424.53MB

11. Appendix/6. How to Code by Yourself (part 2).mp414.8MB

11. Appendix/7. How to Succeed in this Course (Long Version).mp412.99MB

11. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.95MB

11. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp478.27MB

2. Beginner's Corner Working with Word Vectors/1. What are vectors.mp435.35MB

2. Beginner's Corner Working with Word Vectors/2. What is a word analogy.mp431.21MB

2. Beginner's Corner Working with Word Vectors/3. Trying to find and assess word vectors using TF-IDF and t-SNE.mp432.14MB

2. Beginner's Corner Working with Word Vectors/4. Pretrained word vectors from GloVe.mp497.5MB

2. Beginner's Corner Working with Word Vectors/5. Pretrained word vectors from word2vec.mp463.24MB

2. Beginner's Corner Working with Word Vectors/6. Text Classification with word vectors.mp420.62MB

2. Beginner's Corner Working with Word Vectors/7. Text Classification in Code.mp454.6MB

2. Beginner's Corner Working with Word Vectors/8. Using pretrained vectors later in the course.mp413.87MB

3. Review of Language Modeling and Neural Networks/1. Review Section Intro.mp45.55MB

3. Review of Language Modeling and Neural Networks/10. Review Section Summary.mp42.98MB

3. Review of Language Modeling and Neural Networks/2. Bigrams and Language Models.mp412.24MB

3. Review of Language Modeling and Neural Networks/3. Bigrams in Code.mp417.89MB

3. Review of Language Modeling and Neural Networks/4. Neural Bigram Model.mp439.72MB

3. Review of Language Modeling and Neural Networks/5. Neural Bigram Model in Code.mp48.3MB

3. Review of Language Modeling and Neural Networks/6. Neural Network Bigram Model.mp48.03MB

3. Review of Language Modeling and Neural Networks/7. Neural Network Bigram Model in Code.mp45.17MB

3. Review of Language Modeling and Neural Networks/8. Improving Efficiency.mp411.92MB

3. Review of Language Modeling and Neural Networks/9. Improving Efficiency in Code.mp46.75MB

4. Word Embeddings and Word2Vec/1. Return of the Bigram.mp411.5MB

4. Word Embeddings and Word2Vec/10. Word2Vec in Code with Numpy.mp4108.24MB

4. Word Embeddings and Word2Vec/11. Word2Vec Tensorflow Implementation Details.mp412.83MB

4. Word Embeddings and Word2Vec/12. Word2Vec Tensorflow in Code.mp444.15MB

4. Word Embeddings and Word2Vec/13. How to update only part of a Theano shared variable.mp49.19MB

4. Word Embeddings and Word2Vec/14. Word2Vec in Code with Theano.mp431.05MB

4. Word Embeddings and Word2Vec/15. Alternative to Wikipedia Data Brown Corpus.mp412.49MB

4. Word Embeddings and Word2Vec/2. CBOW.mp436.5MB

4. Word Embeddings and Word2Vec/3. Skip-Gram.mp416.06MB

4. Word Embeddings and Word2Vec/4. Hierarchical Softmax.mp431.24MB

4. Word Embeddings and Word2Vec/5. Negative Sampling.mp459.18MB

4. Word Embeddings and Word2Vec/6. Negative Sampling - Important Details.mp418.67MB

4. Word Embeddings and Word2Vec/7. Why do I have 2 word embedding matrices and what do I do with them.mp45.5MB

4. Word Embeddings and Word2Vec/8. Word2Vec implementation tricks.mp415.67MB

4. Word Embeddings and Word2Vec/9. Word2Vec implementation outline.mp414.46MB

5. Word Embeddings using GloVe/1. GloVe Section Introduction.mp417.24MB

5. Word Embeddings using GloVe/10. GloVe in Code - Theano Gradient Descent.mp444.03MB

5. Word Embeddings using GloVe/11. GloVe in Tensorflow with Gradient Descent.mp474.91MB

5. Word Embeddings using GloVe/12. Visualizing country analogies with t-SNE.mp49.18MB

5. Word Embeddings using GloVe/13. Hyperparameter Challenge.mp44.04MB

5. Word Embeddings using GloVe/14. Training GloVe with SVD (Singular Value Decomposition).mp451.98MB

5. Word Embeddings using GloVe/2. Matrix Factorization for Recommender Systems - Basic Concepts.mp490.16MB

5. Word Embeddings using GloVe/3. Matrix Factorization Training.mp428.75MB

5. Word Embeddings using GloVe/4. Expanding the Matrix Factorization Model.mp440.94MB

5. Word Embeddings using GloVe/5. Regularization for Matrix Factorization.mp422.3MB

5. Word Embeddings using GloVe/6. GloVe - Global Vectors for Word Representation.mp47.06MB

5. Word Embeddings using GloVe/7. Recap of ways to train GloVe.mp415.99MB

5. Word Embeddings using GloVe/8. GloVe in Code - Numpy Gradient Descent.mp441.85MB

5. Word Embeddings using GloVe/9. GloVe in Code - Alternating Least Squares.mp411.65MB

6. Unifying Word2Vec and GloVe/1. Pointwise Mutual Information - Word2Vec as Matrix Factorization.mp453.27MB

6. Unifying Word2Vec and GloVe/2. PMI in Code.mp473.12MB

7. Using Neural Networks to Solve NLP Problems/1. Parts-of-Speech (POS) Tagging.mp47.75MB

7. Using Neural Networks to Solve NLP Problems/10. Named Entity Recognition Baseline.mp414.91MB

7. Using Neural Networks to Solve NLP Problems/11. Named Entity Recognition RNN in Theano.mp45.39MB

7. Using Neural Networks to Solve NLP Problems/12. Named Entity Recognition RNN in Tensorflow.mp428.54MB

7. Using Neural Networks to Solve NLP Problems/13. Hyperparameter Challenge II.mp43.83MB

7. Using Neural Networks to Solve NLP Problems/2. How can neural networks be used to solve POS tagging.mp416.88MB

7. Using Neural Networks to Solve NLP Problems/3. Parts-of-Speech Tagging Baseline.mp439.87MB

7. Using Neural Networks to Solve NLP Problems/4. Parts-of-Speech Tagging Recurrent Neural Network in Theano.mp434.81MB

7. Using Neural Networks to Solve NLP Problems/5. Parts-of-Speech Tagging Recurrent Neural Network in Tensorflow.mp4129.45MB

7. Using Neural Networks to Solve NLP Problems/6. How does an HMM solve POS tagging.mp445.24MB

7. Using Neural Networks to Solve NLP Problems/7. Parts-of-Speech Tagging Hidden Markov Model (HMM).mp414.39MB

7. Using Neural Networks to Solve NLP Problems/8. Named Entity Recognition (NER).mp44.96MB

7. Using Neural Networks to Solve NLP Problems/9. Comparing NER and POS tagging.mp414.31MB

8. Recursive Neural Networks (Tree Neural Networks)/1. Recursive Neural Networks Section Introduction.mp437.4MB

8. Recursive Neural Networks (Tree Neural Networks)/10. RNTN in Tensorflow (Code).mp4133.43MB

8. Recursive Neural Networks (Tree Neural Networks)/11. Recursive Neural Network in TensorFlow with Recursion.mp412.74MB

8. Recursive Neural Networks (Tree Neural Networks)/2. Sentences as Trees.mp424.2MB

8. Recursive Neural Networks (Tree Neural Networks)/3. Data Description for Recursive Neural Networks.mp411.54MB

8. Recursive Neural Networks (Tree Neural Networks)/4. What are Recursive Neural Networks Tree Neural Networks (TNNs).mp49.52MB

8. Recursive Neural Networks (Tree Neural Networks)/5. Building a TNN with Recursion.mp48.1MB

8. Recursive Neural Networks (Tree Neural Networks)/6. Trees to Sequences.mp411.17MB

8. Recursive Neural Networks (Tree Neural Networks)/7. Recursive Neural Network in Theano.mp452.51MB

8. Recursive Neural Networks (Tree Neural Networks)/8. Recursive Neural Tensor Networks.mp411.1MB

8. Recursive Neural Networks (Tree Neural Networks)/9. RNTN in Tensorflow (Tips).mp449.51MB

9. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp493.45MB

9. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp487.02MB

9. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp481.45MB

9. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp497.37MB