GetFreeCourses.Co-Udemy-Data Science Transformers for Natural Language Processing

磁力链接/BT种子名称

GetFreeCourses.Co-Udemy-Data Science Transformers for Natural Language Processing

磁力链接/BT种子简介

种子哈希：0c83610b6bd36929682b5042a3507e6c15d4ade3
文件大小： 5.65G
已经下载：4556次
下载速度：极快
收录时间：2024-01-02
最近下载：2024-12-09

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:0C83610B6BD36929682B5042A3507E6C15D4ADE3
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 暗网禁地 91短视频 TikTok成人版 PornHub 草榴社区 乱伦社区

最近搜索

文件列表

  • 4. Fine-Tuning (Intermediate)/9. Fine-Tuning Sentiment Analysis in Python.mp4 137.1 MB
  • 7. Question-Answering (Advanced)/13. From Logits to Answers in Python.mp4 126.5 MB
  • 9. Implement Transformers From Scratch (Advanced)/10. How to Train a Causal Language Model From Scratch.mp4 126.2 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/14. POS Tagging & Custom Datasets (Solution).mp4 120.7 MB
  • 9. Implement Transformers From Scratch (Advanced)/13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).mp4 113.9 MB
  • 13. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 113.4 MB
  • 4. Fine-Tuning (Intermediate)/10. Fine-Tuning Transformers with Custom Dataset.mp4 112.0 MB
  • 7. Question-Answering (Advanced)/7. Aligning the Targets in Python.mp4 108.4 MB
  • 3. Beginner's Corner/4. Sentiment Analysis in Python.mp4 101.8 MB
  • 7. Question-Answering (Advanced)/12. From Logits to Answers.mp4 100.2 MB
  • 9. Implement Transformers From Scratch (Advanced)/12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).mp4 99.8 MB
  • 9. Implement Transformers From Scratch (Advanced)/11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).mp4 98.6 MB
  • 9. Implement Transformers From Scratch (Advanced)/3. How to Implement Multihead Attention From Scratch.mp4 97.9 MB
  • 9. Implement Transformers From Scratch (Advanced)/7. Train and Evaluate Encoder From Scratch.mp4 93.7 MB
  • 3. Beginner's Corner/18. Zero-Shot Classification in Python.mp4 91.9 MB
  • 3. Beginner's Corner/6. Text Generation in Python.mp4 90.5 MB
  • 4. Fine-Tuning (Intermediate)/4. Models and Tokenizers in Python.mp4 88.4 MB
  • 13. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 83.5 MB
  • 3. Beginner's Corner/2. From RNNs to Attention and Transformers - Intuition.mp4 82.0 MB
  • 7. Question-Answering (Advanced)/9. Applying the Tokenizer in Python.mp4 80.2 MB
  • 7. Question-Answering (Advanced)/5. Using the Tokenizer in Python.mp4 75.6 MB
  • 12. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).mp4 75.3 MB
  • 3. Beginner's Corner/10. Named Entity Recognition (NER) in Python.mp4 73.7 MB
  • 12. 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
  • 7. Question-Answering (Advanced)/6. Aligning the Targets.mp4 72.4 MB
  • 3. Beginner's Corner/7. Masked Language Modeling (Article Spinner).mp4 70.6 MB
  • 3. Beginner's Corner/8. Masked Language Modeling (Article Spinner) in Python.mp4 70.3 MB
  • 4. Fine-Tuning (Intermediate)/3. Models and Tokenizers.mp4 67.7 MB
  • 8. Transformers and Attention Theory (Advanced)/3. Self-Attention & Scaled Dot-Product Attention.mp4 67.4 MB
  • 3. Beginner's Corner/14. Neural Machine Translation in Python.mp4 67.2 MB
  • 2. Getting Setup/2. How to use Github & Extra Coding Tips (Optional).mp4 67.0 MB
  • 4. Fine-Tuning (Intermediate)/2. Text Preprocessing and Tokenization Review.mp4 66.2 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/6. Target Alignment (Code).mp4 64.6 MB
  • 4. Fine-Tuning (Intermediate)/5. Transfer Learning & Fine-Tuning (pt 1).mp4 62.7 MB
  • 4. Fine-Tuning (Intermediate)/8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.mp4 61.3 MB
  • 3. Beginner's Corner/5. Text Generation.mp4 59.9 MB
  • 4. Fine-Tuning (Intermediate)/7. Transfer Learning & Fine-Tuning (pt 3).mp4 59.4 MB
  • 4. Fine-Tuning (Intermediate)/13. Fine-Tuning Transformers with Multiple Inputs in Python.mp4 59.4 MB
  • 3. Beginner's Corner/3. Sentiment Analysis.mp4 56.2 MB
  • 11. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.mp4 55.2 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/7. Model Inputs (Code).mp4 53.9 MB
  • 1. Welcome/2. Outline.mp4 53.1 MB
  • 3. Beginner's Corner/1. Beginner's Corner Section Introduction.mp4 52.2 MB
  • 8. Transformers and Attention Theory (Advanced)/10. Decoder Architecture.mp4 52.0 MB
  • 4. Fine-Tuning (Intermediate)/6. Transfer Learning & Fine-Tuning (pt 2).mp4 51.7 MB
  • 12. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).mp4 51.5 MB
  • 3. Beginner's Corner/16. Question Answering in Python.mp4 50.5 MB
  • 3. Beginner's Corner/12. Text Summarization in Python.mp4 47.7 MB
  • 7. Question-Answering (Advanced)/8. Applying the Tokenizer.mp4 47.2 MB
  • 7. Question-Answering (Advanced)/15. Computing Metrics in Python.mp4 46.4 MB
  • 11. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 45.7 MB
  • 2. Getting Setup/1. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 45.7 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/9. Translation Metrics (BLEU Score & BERT Score) (Code).mp4 45.4 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/4. Target Alignment (Code Preparation).mp4 45.1 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/3. Data & Tokenizer (Code).mp4 44.8 MB
  • 2. Getting Setup/5. How to Succeed in This Course.mp4 43.2 MB
  • 4. Fine-Tuning (Intermediate)/11. Hugging Face AutoConfig.mp4 42.8 MB
  • 3. Beginner's Corner/15. Question Answering.mp4 42.0 MB
  • 14. Appendix FAQ Finale/2. BONUS.mp4 41.9 MB
  • 7. Question-Answering (Advanced)/3. Exploring the Dataset (SQuAD) in Python.mp4 41.8 MB
  • 8. Transformers and Attention Theory (Advanced)/11. Encoder-Decoder Architecture.mp4 41.6 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/10. Metrics (Code).mp4 41.2 MB
  • 9. Implement Transformers From Scratch (Advanced)/8. How to Implement Causal Self-Attention From Scratch.mp4 41.1 MB
  • 13. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
  • 7. Question-Answering (Advanced)/17. Train and Evaluate in Python.mp4 39.6 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/5. Aside Seq2Seq Basics (Optional).mp4 38.9 MB
  • 8. Transformers and Attention Theory (Advanced)/2. Basic Self-Attention.mp4 38.8 MB
  • 9. Implement Transformers From Scratch (Advanced)/5. How to Implement Positional Encoding From Scratch.mp4 37.6 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/1. Token Classification Section Introduction.mp4 37.6 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/11. Train & Evaluate (Code).mp4 37.5 MB
  • 1. Welcome/1. Introduction.mp4 36.3 MB
  • 7. Question-Answering (Advanced)/4. Using the Tokenizer.mp4 36.2 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/4. Data & Tokenizer (Code).mp4 35.8 MB
  • 8. Transformers and Attention Theory (Advanced)/6. Multi-Head Attention.mp4 35.3 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/9. Metrics (Code Preparation).mp4 35.1 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/6. Model Inputs (Code Preparation).mp4 34.0 MB
  • 8. Transformers and Attention Theory (Advanced)/13. GPT.mp4 32.7 MB
  • 3. Beginner's Corner/17. Zero-Shot Classification.mp4 31.6 MB
  • 8. Transformers and Attention Theory (Advanced)/14. GPT-2.mp4 31.1 MB
  • 8. Transformers and Attention Theory (Advanced)/7. Transformer Block.mp4 30.9 MB
  • 8. Transformers and Attention Theory (Advanced)/8. Positional Encodings.mp4 30.4 MB
  • 4. Fine-Tuning (Intermediate)/12. Fine-Tuning with Multiple Inputs (Textual Entailment).mp4 29.8 MB
  • 3. Beginner's Corner/13. Neural Machine Translation.mp4 29.5 MB
  • 9. Implement Transformers From Scratch (Advanced)/9. How to Implement a Transformer Decoder (GPT) From Scratch.mp4 28.6 MB
  • 3. Beginner's Corner/20. Suggestion Box.mp4 28.5 MB
  • 9. Implement Transformers From Scratch (Advanced)/6. How to Implement Transformer Encoder From Scratch.mp4 28.3 MB
  • 2. Getting Setup/4. Are You Beginner, Intermediate, or Advanced All are OK!.mp4 28.0 MB
  • 9. Implement Transformers From Scratch (Advanced)/1. Implementation Section Introduction.mp4 26.8 MB
  • 8. Transformers and Attention Theory (Advanced)/9. Encoder Architecture.mp4 26.4 MB
  • 7. Question-Answering (Advanced)/14. Computing Metrics.mp4 26.2 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/2. Data & Tokenizer (Code Preparation).mp4 25.7 MB
  • 3. Beginner's Corner/11. Text Summarization.mp4 25.3 MB
  • 8. Transformers and Attention Theory (Advanced)/15. GPT-3.mp4 25.2 MB
  • 8. Transformers and Attention Theory (Advanced)/12. BERT.mp4 24.4 MB
  • 3. Beginner's Corner/19. Beginner's Corner Section Summary.mp4 24.3 MB
  • 9. Implement Transformers From Scratch (Advanced)/2. Encoder Implementation Plan & Outline.mp4 24.1 MB
  • 7. Question-Answering (Advanced)/11. Question-Answering Metrics in Python.mp4 24.0 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/12. Model and Trainer (Code).mp4 23.3 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/7. Data Collator (Code Preparation).mp4 23.2 MB
  • 3. Beginner's Corner/9. Named Entity Recognition (NER).mp4 23.1 MB
  • 8. Transformers and Attention Theory (Advanced)/4. Attention Efficiency.mp4 22.6 MB
  • 7. Question-Answering (Advanced)/1. Question-Answering Section Introduction.mp4 22.6 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/13. POS Tagging & Custom Datasets (Exercise Prompt).mp4 22.4 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/10. Train & Evaluate (Code Preparation).mp4 22.3 MB
  • 8. Transformers and Attention Theory (Advanced)/16. Theory Section Summary.mp4 22.0 MB
  • 4. Fine-Tuning (Intermediate)/1. Fine-Tuning Section Introduction.mp4 21.1 MB
  • 7. Question-Answering (Advanced)/2. Exploring the Dataset (SQuAD).mp4 21.1 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/2. Data & Tokenizer (Code Preparation).mp4 20.3 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).mp4 20.2 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/5. Create Tokenized Dataset (Code Preparation).mp4 19.2 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/1. Translation Section Introduction.mp4 19.1 MB
  • 13. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).mp4 18.7 MB
  • 2. Getting Setup/3. Where to get the code, notebooks, and data.mp4 18.6 MB
  • 8. Transformers and Attention Theory (Advanced)/1. Theory Section Introduction.mp4 18.0 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/8. Data Collator (Code).mp4 17.8 MB
  • 7. Question-Answering (Advanced)/10. Question-Answering Metrics.mp4 17.3 MB
  • 14. Appendix FAQ Finale/1. What is the Appendix.mp4 17.2 MB
  • 4. Fine-Tuning (Intermediate)/14. Fine-Tuning Section Summary.mp4 16.5 MB
  • 8. Transformers and Attention Theory (Advanced)/5. Attention Mask.mp4 15.8 MB
  • 9. Implement Transformers From Scratch (Advanced)/4. How to Implement the Transformer Block From Scratch.mp4 15.7 MB
  • 7. Question-Answering (Advanced)/18. Question-Answering Section Summary.mp4 14.9 MB
  • 7. Question-Answering (Advanced)/16. Train and Evaluate.mp4 14.8 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/11. Model and Trainer (Code Preparation).mp4 11.3 MB
  • 9. Implement Transformers From Scratch (Advanced)/14. Implementation Section Summary.mp4 11.1 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/12. Translation Section Summary.mp4 10.2 MB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/15. Token Classification Section Summary.mp4 8.4 MB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/3. Things Move Fast.mp4 6.4 MB
  • 13. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 33.5 kB
  • 7. Question-Answering (Advanced)/12. From Logits to Answers.srt 28.4 kB
  • 3. Beginner's Corner/2. From RNNs to Attention and Transformers - Intuition.srt 24.6 kB
  • 8. Transformers and Attention Theory (Advanced)/3. Self-Attention & Scaled Dot-Product Attention.srt 24.5 kB
  • 13. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt 24.5 kB
  • 12. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).srt 23.7 kB
  • 3. Beginner's Corner/4. Sentiment Analysis in Python.srt 21.6 kB
  • 4. Fine-Tuning (Intermediate)/3. Models and Tokenizers.srt 21.1 kB
  • 11. Setting Up Your Environment FAQ/1. Anaconda Environment Setup.srt 20.6 kB
  • 9. Implement Transformers From Scratch (Advanced)/10. How to Train a Causal Language Model From Scratch.srt 20.6 kB
  • 7. Question-Answering (Advanced)/6. Aligning the Targets.srt 19.8 kB
  • 4. Fine-Tuning (Intermediate)/9. Fine-Tuning Sentiment Analysis in Python.srt 19.7 kB
  • 7. Question-Answering (Advanced)/7. Aligning the Targets in Python.srt 19.3 kB
  • 4. Fine-Tuning (Intermediate)/2. Text Preprocessing and Tokenization Review.srt 18.7 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/14. POS Tagging & Custom Datasets (Solution).srt 18.3 kB
  • 9. Implement Transformers From Scratch (Advanced)/13. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 3).srt 17.9 kB
  • 13. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt 17.6 kB
  • 7. Question-Answering (Advanced)/13. From Logits to Answers in Python.srt 17.3 kB
  • 4. Fine-Tuning (Intermediate)/8. Fine-Tuning Sentiment Analysis and the GLUE Benchmark.srt 17.3 kB
  • 3. Beginner's Corner/18. Zero-Shot Classification in Python.srt 16.8 kB
  • 3. Beginner's Corner/7. Masked Language Modeling (Article Spinner).srt 16.5 kB
  • 11. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 16.2 kB
  • 2. Getting Setup/2. How to use Github & Extra Coding Tips (Optional).srt 16.1 kB
  • 9. Implement Transformers From Scratch (Advanced)/3. How to Implement Multihead Attention From Scratch.srt 15.9 kB
  • 3. Beginner's Corner/5. Text Generation.srt 15.8 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/5. Aside Seq2Seq Basics (Optional).srt 15.6 kB
  • 4. Fine-Tuning (Intermediate)/10. Fine-Tuning Transformers with Custom Dataset.srt 15.5 kB
  • 3. Beginner's Corner/1. Beginner's Corner Section Introduction.srt 15.4 kB
  • 9. Implement Transformers From Scratch (Advanced)/12. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 2).srt 15.3 kB
  • 12. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.srt 15.3 kB
  • 3. Beginner's Corner/6. Text Generation in Python.srt 15.3 kB
  • 8. Transformers and Attention Theory (Advanced)/10. Decoder Architecture.srt 15.0 kB
  • 4. Fine-Tuning (Intermediate)/6. Transfer Learning & Fine-Tuning (pt 2).srt 14.9 kB
  • 3. Beginner's Corner/3. Sentiment Analysis.srt 14.9 kB
  • 13. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).srt 14.9 kB
  • 4. Fine-Tuning (Intermediate)/4. Models and Tokenizers in Python.srt 14.5 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/4. Target Alignment (Code Preparation).srt 14.1 kB
  • 4. Fine-Tuning (Intermediate)/7. Transfer Learning & Fine-Tuning (pt 3).srt 14.0 kB
  • 1. Welcome/2. Outline.srt 13.8 kB
  • 9. Implement Transformers From Scratch (Advanced)/11. Implement a Seq2Seq Transformer From Scratch for Language Translation (pt 1).srt 13.7 kB
  • 12. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).srt 13.6 kB
  • 7. Question-Answering (Advanced)/5. Using the Tokenizer in Python.srt 13.4 kB
  • 2. Getting Setup/5. How to Succeed in This Course.srt 13.3 kB
  • 4. Fine-Tuning (Intermediate)/5. Transfer Learning & Fine-Tuning (pt 1).srt 13.0 kB
  • 8. Transformers and Attention Theory (Advanced)/2. Basic Self-Attention.srt 12.7 kB
  • 9. Implement Transformers From Scratch (Advanced)/7. Train and Evaluate Encoder From Scratch.srt 12.6 kB
  • 7. Question-Answering (Advanced)/8. Applying the Tokenizer.srt 12.6 kB
  • 7. Question-Answering (Advanced)/9. Applying the Tokenizer in Python.srt 12.3 kB
  • 2. Getting Setup/1. Get Your Hands Dirty, Practical Coding Experience, Data Links.srt 12.3 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/6. Target Alignment (Code).srt 12.1 kB
  • 8. Transformers and Attention Theory (Advanced)/11. Encoder-Decoder Architecture.srt 11.6 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/6. Model Inputs (Code Preparation).srt 11.5 kB
  • 7. Question-Answering (Advanced)/4. Using the Tokenizer.srt 11.1 kB
  • 4. Fine-Tuning (Intermediate)/12. Fine-Tuning with Multiple Inputs (Textual Entailment).srt 10.6 kB
  • 3. Beginner's Corner/15. Question Answering.srt 10.3 kB
  • 3. Beginner's Corner/14. Neural Machine Translation in Python.srt 10.0 kB
  • 3. Beginner's Corner/10. Named Entity Recognition (NER) in Python.srt 9.9 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/1. Token Classification Section Introduction.srt 9.8 kB
  • 8. Transformers and Attention Theory (Advanced)/7. Transformer Block.srt 9.8 kB
  • 8. Transformers and Attention Theory (Advanced)/8. Positional Encodings.srt 9.7 kB
  • 8. Transformers and Attention Theory (Advanced)/6. Multi-Head Attention.srt 9.6 kB
  • 3. Beginner's Corner/8. Masked Language Modeling (Article Spinner) in Python.srt 9.5 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/3. Data & Tokenizer (Code).srt 9.4 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/9. Metrics (Code Preparation).srt 9.4 kB
  • 8. Transformers and Attention Theory (Advanced)/13. GPT.srt 8.9 kB
  • 8. Transformers and Attention Theory (Advanced)/9. Encoder Architecture.srt 8.8 kB
  • 9. Implement Transformers From Scratch (Advanced)/1. Implementation Section Introduction.srt 8.7 kB
  • 9. Implement Transformers From Scratch (Advanced)/2. Encoder Implementation Plan & Outline.srt 8.6 kB
  • 8. Transformers and Attention Theory (Advanced)/14. GPT-2.srt 8.5 kB
  • 3. Beginner's Corner/13. Neural Machine Translation.srt 8.3 kB
  • 14. Appendix FAQ Finale/2. BONUS.srt 8.1 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/7. Model Inputs (Code).srt 8.0 kB
  • 3. Beginner's Corner/17. Zero-Shot Classification.srt 7.8 kB
  • 3. Beginner's Corner/12. Text Summarization in Python.srt 7.7 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/2. Data & Tokenizer (Code Preparation).srt 7.7 kB
  • 2. Getting Setup/4. Are You Beginner, Intermediate, or Advanced All are OK!.srt 7.3 kB
  • 3. Beginner's Corner/11. Text Summarization.srt 7.3 kB
  • 3. Beginner's Corner/16. Question Answering in Python.srt 7.1 kB
  • 8. Transformers and Attention Theory (Advanced)/1. Theory Section Introduction.srt 7.0 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/13. POS Tagging & Custom Datasets (Exercise Prompt).srt 7.0 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/2. Data & Tokenizer (Code Preparation).srt 7.0 kB
  • 7. Question-Answering (Advanced)/14. Computing Metrics.srt 6.8 kB
  • 4. Fine-Tuning (Intermediate)/13. Fine-Tuning Transformers with Multiple Inputs in Python.srt 6.8 kB
  • 8. Transformers and Attention Theory (Advanced)/15. GPT-3.srt 6.7 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/4. Data & Tokenizer (Code).srt 6.6 kB
  • 3. Beginner's Corner/19. Beginner's Corner Section Summary.srt 6.5 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/1. Translation Section Introduction.srt 6.5 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/9. Translation Metrics (BLEU Score & BERT Score) (Code).srt 6.5 kB
  • 8. Transformers and Attention Theory (Advanced)/16. Theory Section Summary.srt 6.4 kB
  • 9. Implement Transformers From Scratch (Advanced)/5. How to Implement Positional Encoding From Scratch.srt 6.4 kB
  • 3. Beginner's Corner/9. Named Entity Recognition (NER).srt 6.4 kB
  • 4. Fine-Tuning (Intermediate)/1. Fine-Tuning Section Introduction.srt 6.3 kB
  • 8. Transformers and Attention Theory (Advanced)/12. BERT.srt 6.3 kB
  • 7. Question-Answering (Advanced)/1. Question-Answering Section Introduction.srt 6.3 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/10. Metrics (Code).srt 6.2 kB
  • 7. Question-Answering (Advanced)/15. Computing Metrics in Python.srt 6.2 kB
  • 4. Fine-Tuning (Intermediate)/11. Hugging Face AutoConfig.srt 6.2 kB
  • 8. Transformers and Attention Theory (Advanced)/4. Attention Efficiency.srt 6.0 kB
  • 7. Question-Answering (Advanced)/2. Exploring the Dataset (SQuAD).srt 5.8 kB
  • 9. Implement Transformers From Scratch (Advanced)/8. How to Implement Causal Self-Attention From Scratch.srt 5.8 kB
  • 1. Welcome/1. Introduction.srt 5.8 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/10. Train & Evaluate (Code Preparation).srt 5.8 kB
  • 7. Question-Answering (Advanced)/18. Question-Answering Section Summary.srt 5.2 kB
  • 8. Transformers and Attention Theory (Advanced)/5. Attention Mask.srt 5.2 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/5. Create Tokenized Dataset (Code Preparation).srt 5.1 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/8. Translation Metrics (BLEU Score & BERT Score) (Code Preparation).srt 5.1 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/7. Data Collator (Code Preparation).srt 5.0 kB
  • 9. Implement Transformers From Scratch (Advanced)/9. How to Implement a Transformer Decoder (GPT) From Scratch.srt 5.0 kB
  • 3. Beginner's Corner/20. Suggestion Box.srt 4.9 kB
  • 9. Implement Transformers From Scratch (Advanced)/6. How to Implement Transformer Encoder From Scratch.srt 4.9 kB
  • 7. Question-Answering (Advanced)/10. Question-Answering Metrics.srt 4.8 kB
  • 7. Question-Answering (Advanced)/17. Train and Evaluate in Python.srt 4.8 kB
  • 7. Question-Answering (Advanced)/3. Exploring the Dataset (SQuAD) in Python.srt 4.8 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/11. Train & Evaluate (Code).srt 4.7 kB
  • 2. Getting Setup/3. Where to get the code, notebooks, and data.srt 4.4 kB
  • 4. Fine-Tuning (Intermediate)/14. Fine-Tuning Section Summary.srt 4.2 kB
  • 14. Appendix FAQ Finale/1. What is the Appendix.srt 4.0 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/8. Data Collator (Code).srt 3.8 kB
  • 7. Question-Answering (Advanced)/16. Train and Evaluate.srt 3.4 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/12. Translation Section Summary.srt 3.4 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/12. Model and Trainer (Code).srt 3.2 kB
  • 7. Question-Answering (Advanced)/11. Question-Answering Metrics in Python.srt 3.0 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/11. Model and Trainer (Code Preparation).srt 3.0 kB
  • 5. Named Entity Recognition (NER) and POS Tagging (Intermediate)/15. Token Classification Section Summary.srt 2.7 kB
  • 9. Implement Transformers From Scratch (Advanced)/4. How to Implement the Transformer Block From Scratch.srt 2.4 kB
  • 6. Seq2Seq and Neural Machine Translation (Intermediate)/3. Things Move Fast.srt 2.4 kB
  • 9. Implement Transformers From Scratch (Advanced)/14. Implementation Section Summary.srt 2.0 kB
  • 10. Extras/1. Data Links.html 256 Bytes
  • How you can help GetFreeCourses.Co.txt 182 Bytes
  • 2. Getting Setup/1.1 Data Links.html 157 Bytes
  • 2. Getting Setup/3.2 Data Links.html 157 Bytes
  • 2. Getting Setup/1.2 Github Link.html 145 Bytes
  • 2. Getting Setup/3.3 Github Link.html 145 Bytes
  • 2. Getting Setup/3.1 Code Link.html 125 Bytes
  • 11. Setting Up Your Environment FAQ/GetFreeCourses.Co.url 116 Bytes
  • 13. Effective Learning Strategies for Machine Learning FAQ/GetFreeCourses.Co.url 116 Bytes
  • 4. Fine-Tuning (Intermediate)/GetFreeCourses.Co.url 116 Bytes
  • 7. Question-Answering (Advanced)/GetFreeCourses.Co.url 116 Bytes
  • Download Paid Udemy Courses For Free.url 116 Bytes
  • GetFreeCourses.Co.url 116 Bytes

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！
>