TGx:[UdemyCourseDownloader] Deep Learning Advanced NLP and RNNs

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[UdemyCourseDownloader] Deep Learning Advanced NLP and RNNs

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Category:

Other > Training

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English

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3.01 GB

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b9085bc5426b3ff97d2c7a07a517b5f7b5ce8f1c

Added By:

kirat1h

Added:

27-11-2018 18:18

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1,225

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File	Size
1. Welcome/1. Introduction.mp4	14.42 MB
1. Welcome/1. Introduction.vtt	3.34 kB
1. Welcome/2. Outline.mp4	16.14 MB
1. Welcome/2. Outline.vtt	5.21 kB
1. Welcome/3. Where to get the code.mp4	19.58 MB
1. Welcome/3. Where to get the code.vtt	5.73 kB
1. Welcome/4. How to Succeed in this Course.mp4	17.41 MB
1. Welcome/4. How to Succeed in this Course.vtt	3.49 kB
2. Review/1. Review Section Introduction.mp4	20.75 MB
2. Review/1. Review Section Introduction.vtt	5.29 kB
2. Review/10. Different Types of RNN Tasks.mp4	56.79 MB
2. Review/10. Different Types of RNN Tasks.vtt	13.46 kB
2. Review/11. A Simple RNN Experiment.mp4	56.00 MB
2. Review/11. A Simple RNN Experiment.vtt	6.65 kB
2. Review/12. RNN Code.mp4	31.10 MB
2. Review/12. RNN Code.vtt	3.70 kB
2. Review/13. Review Section Summary.mp4	19.64 MB
2. Review/13. Review Section Summary.vtt	5.59 kB
2. Review/2. What is a word embedding.mp4	57.53 MB
2. Review/2. What is a word embedding.vtt	16.66 kB
2. Review/3. Using word embeddings.mp4	18.67 MB
2. Review/3. Using word embeddings.vtt	5.39 kB
2. Review/4. What is a CNN.mp4	61.97 MB
2. Review/4. What is a CNN.vtt	15.69 kB
2. Review/5. Where to get the data.mp4	27.15 MB
2. Review/5. Where to get the data.vtt	5.68 kB
2. Review/6. CNN Code (part 1).mp4	148.61 MB
2. Review/6. CNN Code (part 1).vtt	17.47 kB
2. Review/7. CNN Code (part 2).mp4	59.29 MB
2. Review/7. CNN Code (part 2).vtt	6.90 kB
2. Review/8. What is an RNN.mp4	56.61 MB
2. Review/8. What is an RNN.vtt	15.12 kB
2. Review/9. GRUs and LSTMs.mp4	49.64 MB
2. Review/9. GRUs and LSTMs.vtt	12.15 kB
3. Bidirectional RNNs/1. Bidirectional RNNs Motivation.mp4	33.35 MB
3. Bidirectional RNNs/1. Bidirectional RNNs Motivation.vtt	9.23 kB
3. Bidirectional RNNs/2. Bidirectional RNN Experiment.mp4	48.70 MB
3. Bidirectional RNNs/2. Bidirectional RNN Experiment.vtt	5.18 kB
3. Bidirectional RNNs/3. Bidirectional RNN Code.mp4	22.72 MB
3. Bidirectional RNNs/3. Bidirectional RNN Code.vtt	2.42 kB
3. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.mp4	32.78 MB
3. Bidirectional RNNs/4. Image Classification with Bidirectional RNNs.vtt	6.75 kB
3. Bidirectional RNNs/5. Image Classification Code.mp4	48.62 MB
3. Bidirectional RNNs/5. Image Classification Code.vtt	5.81 kB
3. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.mp4	13.99 MB
3. Bidirectional RNNs/6. Bidirectional RNNs Section Summary.vtt	2.67 kB
4. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.mp4	32.51 MB
4. Sequence-to-sequence models (Seq2Seq)/1. Seq2Seq Theory.vtt	8.11 kB
4. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.mp4	16.12 MB
4. Sequence-to-sequence models (Seq2Seq)/2. Seq2Seq Applications.vtt	3.83 kB
4. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.mp4	31.13 MB
4. Sequence-to-sequence models (Seq2Seq)/3. Decoding in Detail and Teacher Forcing.vtt	7.55 kB
4. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.mp4	12.47 MB
4. Sequence-to-sequence models (Seq2Seq)/4. Poetry Revisited.vtt	3.72 kB
4. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.mp4	82.59 MB
4. Sequence-to-sequence models (Seq2Seq)/5. Poetry Revisited Code 1.vtt	9.50 kB
4. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.mp4	66.56 MB
4. Sequence-to-sequence models (Seq2Seq)/6. Poetry Revisited Code 2.vtt	7.46 kB
4. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.mp4	84.34 MB
4. Sequence-to-sequence models (Seq2Seq)/7. Seq2Seq in Code 1.vtt	8.33 kB
4. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.mp4	50.59 MB
4. Sequence-to-sequence models (Seq2Seq)/8. Seq2Seq in Code 2.vtt	5.42 kB
4. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.mp4	13.63 MB
4. Sequence-to-sequence models (Seq2Seq)/9. Seq2Seq Section Summary.vtt	3.31 kB
5. Attention/1. Attention Section Introduction.mp4	8.41 MB
5. Attention/1. Attention Section Introduction.vtt	2.65 kB
5. Attention/2. Attention Theory.mp4	61.82 MB
5. Attention/2. Attention Theory.vtt	20.86 kB
5. Attention/3. Teacher Forcing.mp4	7.18 MB
5. Attention/3. Teacher Forcing.vtt	2.25 kB
5. Attention/4. Helpful Implementation Details.mp4	40.88 MB
5. Attention/4. Helpful Implementation Details.vtt	13.11 kB
5. Attention/5. Attention Code 1.mp4	99.94 MB
5. Attention/5. Attention Code 1.vtt	10.28 kB
5. Attention/6. Attention Code 2.mp4	41.60 MB
5. Attention/6. Attention Code 2.vtt	3.69 kB
5. Attention/7. Visualizing Attention.mp4	10.43 MB
5. Attention/7. Visualizing Attention.vtt	2.71 kB
5. Attention/8. Building a Chatbot without any more Code.mp4	76.15 MB
5. Attention/8. Building a Chatbot without any more Code.vtt	10.08 kB
5. Attention/9. Attention Section Summary.mp4	13.88 MB
5. Attention/9. Attention Section Summary.vtt	3.94 kB
6. Memory Networks/1. Memory Networks Section Introduction.mp4	39.23 MB
6. Memory Networks/1. Memory Networks Section Introduction.vtt	11.06 kB
6. Memory Networks/2. Memory Networks Theory.mp4	30.40 MB
6. Memory Networks/2. Memory Networks Theory.vtt	10.70 kB
6. Memory Networks/3. Memory Networks Code 1.mp4	79.62 MB
6. Memory Networks/3. Memory Networks Code 1.vtt	8.40 kB
6. Memory Networks/4. Memory Networks Code 2.mp4	53.55 MB
6. Memory Networks/4. Memory Networks Code 2.vtt	5.19 kB
6. Memory Networks/5. Memory Networks Code 3.mp4	55.85 MB
6. Memory Networks/5. Memory Networks Code 3.vtt	6.15 kB
6. Memory Networks/6. Memory Networks Section Summary.mp4	16.11 MB
6. Memory Networks/6. Memory Networks Section Summary.vtt	4.35 kB
7. Basics Review/1. (Review) Keras Discussion.mp4	27.64 MB
7. Basics Review/1. (Review) Keras Discussion.vtt	8.05 kB
7. Basics Review/2. (Review) Keras Neural Network in Code.mp4	66.11 MB
7. Basics Review/2. (Review) Keras Neural Network in Code.vtt	6.47 kB
7. Basics Review/3. (Review) Keras Functional API.mp4	38.60 MB
7. Basics Review/3. (Review) Keras Functional API.vtt	4.70 kB
8. Appendix/1. What is the Appendix.mp4	17.68 MB
8. Appendix/1. What is the Appendix.vtt	3.27 kB
8. Appendix/10. What order should I take your courses in (part 2).mp4	122.65 MB
8. Appendix/10. What order should I take your courses in (part 2).vtt	20.29 kB
8. Appendix/11. Python 2 vs Python 3.mp4	18.79 MB
8. Appendix/11. Python 2 vs Python 3.vtt	5.34 kB
8. Appendix/12. BONUS Where to get discount coupons and FREE deep learning material.mp4	13.07 MB
8. Appendix/12. BONUS Where to get discount coupons and FREE deep learning material.vtt	2.99 kB
8. Appendix/2. Windows-Focused Environment Setup 2018.mp4	193.26 MB
8. Appendix/2. Windows-Focused Environment Setup 2018.vtt	17.38 kB
8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....mp4	166.45 MB
8. Appendix/3. How to How to install Numpy, Theano, Tensorflow, etc....vtt	12.41 kB
8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4	115.85 MB
8. Appendix/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt	27.96 kB
8. Appendix/5. How to Succeed in this Course (Long Version).mp4	39.01 MB
8. Appendix/5. How to Succeed in this Course (Long Version).vtt	12.84 kB
8. Appendix/6. How to Code by Yourself (part 1).mp4	82.11 MB
8. Appendix/6. How to Code by Yourself (part 1).vtt	19.61 kB
8. Appendix/7. How to Code by Yourself (part 2).mp4	56.22 MB
8. Appendix/7. How to Code by Yourself (part 2).vtt	11.62 kB
8. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4	78.26 MB
8. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt	12.22 kB
8. Appendix/9. What order should I take your courses in (part 1).mp4	88.04 MB
8. Appendix/9. What order should I take your courses in (part 1).vtt	14.17 kB
[FreeCoursesOnline.Me].url	133.00 B
[FreeTutorials.Eu].url	129.00 B
[FTU Forum].url	1.34 kB

Description

Description
It’s hard to believe it's been been over a year since I released my first course on Deep Learning with NLP (natural language processing).

A lot of cool stuff has happened since then, and I've been deep in the trenches learning, researching, and accumulating the best and most useful ideas to bring them back to you.

So what is this course all about, and how have things changed since then?

In previous courses, you learned about some of the fundamental building blocks of Deep NLP. We looked at RNNs (recurrent neural networks), CNNs (convolutional neural networks), and word embedding algorithms such as