Udemy - Deep Learning Convolutional Neural Networks in Python (5.2025)

磁力链接/BT种子名称

Udemy - Deep Learning Convolutional Neural Networks in Python (5.2025)

磁力链接/BT种子简介

种子哈希：05df7c021b6cdc5cc56ebb4fbade372d24b5e8e5
文件大小： 3.96G
已经下载：382次
下载速度：极快
收录时间：2025-07-07
最近下载：2025-08-14

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:05DF7C021B6CDC5CC56EBB4FBADE372D24B5E8E5
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 世界之窗 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 极乐禁地 91短视频 TikTok成人版 PornHub 草榴社区 哆哔涩漫 呦乐园 萝莉岛

最近搜索

文件列表

  • 13. Setting Up Your Environment (FAQ by Student Request)/2. Anaconda Environment Setup.mp4 324.1 MB
  • 06. Natural Language Processing (NLP)/5. Text Classification with CNNs.mp4 313.4 MB
  • 05. Convolutional Neural Networks/4. Why use 0-indexing.mp4 210.7 MB
  • 13. Setting Up Your Environment (FAQ by Student Request)/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 201.3 MB
  • 03. Machine Learning and Neurons/4. Classification Notebook.mp4 180.5 MB
  • 15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 143.0 MB
  • 15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 141.4 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/8. Proof that using Jupyter Notebook is the same as not using it.mp4 113.7 MB
  • 02. Google Colab/2. Uploading your own data to Google Colab.mp4 108.3 MB
  • 05. Convolutional Neural Networks/12. Improving CIFAR-10 Results (Legacy).mp4 106.1 MB
  • 04. Feedforward Artificial Neural Networks/10. ANN for Regression.mp4 104.0 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/5. How to Code by Yourself (part 1).mp4 98.1 MB
  • 03. Machine Learning and Neurons/6. Regression Notebook.mp4 91.8 MB
  • 02. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 75.1 MB
  • 03. Machine Learning and Neurons/8. How does a model learn.mp4 63.5 MB
  • 15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 63.1 MB
  • 05. Convolutional Neural Networks/6. CNN Architecture.mp4 62.6 MB
  • 04. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 62.4 MB
  • 06. Natural Language Processing (NLP)/3. Text Preprocessing.mp4 62.3 MB
  • 05. Convolutional Neural Networks/7. CNN Code Preparation.mp4 60.4 MB
  • 03. Machine Learning and Neurons/2. What is Machine Learning.mp4 50.3 MB
  • 05. Convolutional Neural Networks/5. Convolution on Color Images.mp4 48.1 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. How to use Github & Extra Coding Tips (Optional).mp4 46.6 MB
  • 04. Feedforward Artificial Neural Networks/9. ANN for Image Classification.mp4 46.5 MB
  • 06. Natural Language Processing (NLP)/2. Code Preparation (NLP).mp4 46.5 MB
  • 05. Convolutional Neural Networks/1. What is Convolution (part 1).mp4 45.5 MB
  • 16. Appendix FAQ Finale/1. BONUS.mp4 45.3 MB
  • 04. Feedforward Artificial Neural Networks/6. How to Represent Images.mp4 45.2 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. Beginner's Coding Tips.mp4 44.9 MB
  • 03. Machine Learning and Neurons/10. Saving and Loading a Model.mp4 43.7 MB
  • 03. Machine Learning and Neurons/11. Suggestion Box.mp4 41.7 MB
  • 05. Convolutional Neural Networks/8. CNN for Fashion MNIST.mp4 40.4 MB
  • 11. In-Depth Gradient Descent/5. Adam (pt 1).mp4 40.0 MB
  • 03. Machine Learning and Neurons/3. Code Preparation (Classification Theory).mp4 39.6 MB
  • 09. Practical Tips/1. Advanced CNNs and how to Design your Own.mp4 39.1 MB
  • 08. Convolutional Neural Network Description/2. Tracking Shapes in a CNN.mp4 38.9 MB
  • 02. Google Colab/3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 38.3 MB
  • 07. Convolution In-Depth/1. Real-Life Examples of Convolution.mp4 37.9 MB
  • 06. Natural Language Processing (NLP)/1. Embeddings.mp4 37.7 MB
  • 04. Feedforward Artificial Neural Networks/8. Code Preparation (ANN).mp4 33.9 MB
  • 02. Google Colab/4. Temporary 403 Errors.mp4 33.2 MB
  • 11. In-Depth Gradient Descent/6. Adam (pt 2).mp4 32.8 MB
  • 04. Feedforward Artificial Neural Networks/5. Multiclass Classification.mp4 32.3 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Where To Get the Code Troubleshooting.mp4 31.1 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/6. How to Code by Yourself (part 2).mp4 30.7 MB
  • 04. Feedforward Artificial Neural Networks/3. The Geometrical Picture.mp4 30.1 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/10. Is Theano Dead.mp4 29.3 MB
  • 03. Machine Learning and Neurons/7. The Neuron.mp4 27.6 MB
  • 05. Convolutional Neural Networks/9. CNN for CIFAR-10.mp4 27.0 MB
  • 05. Convolutional Neural Networks/10. Data Augmentation.mp4 27.0 MB
  • 11. In-Depth Gradient Descent/3. Momentum.mp4 26.8 MB
  • 04. Feedforward Artificial Neural Networks/2. Forward Propagation.mp4 26.8 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 26.6 MB
  • 15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).mp4 26.1 MB
  • 10. In-Depth Loss Functions/1. Mean Squared Error.mp4 25.2 MB
  • 03. Machine Learning and Neurons/9. Making Predictions.mp4 24.7 MB
  • 11. In-Depth Gradient Descent/4. Variable and Adaptive Learning Rates.mp4 24.6 MB
  • 08. Convolutional Neural Network Description/1. Convolution on 3-D Images.mp4 22.8 MB
  • 06. Natural Language Processing (NLP)/4. CNNs for Text.mp4 22.6 MB
  • 07. Convolution In-Depth/3. Alternative Views on Convolution.mp4 22.5 MB
  • 11. In-Depth Gradient Descent/1. Gradient Descent.mp4 21.8 MB
  • 10. In-Depth Loss Functions/3. Categorical Cross Entropy.mp4 20.5 MB
  • 04. Feedforward Artificial Neural Networks/1. Artificial Neural Networks Section Introduction.mp4 19.3 MB
  • 12. Appendix FAQ Intro/1. What is the Appendix.mp4 19.2 MB
  • 11. In-Depth Gradient Descent/2. Stochastic Gradient Descent.mp4 19.1 MB
  • 07. Convolution In-Depth/2. Beginner's Guide to Convolution.mp4 18.4 MB
  • 03. Machine Learning and Neurons/5. Code Preparation (Regression Theory).mp4 17.7 MB
  • 05. Convolutional Neural Networks/3. What is Convolution (part 3).mp4 17.0 MB
  • 05. Convolutional Neural Networks/2. What is Convolution (part 2).mp4 15.2 MB
  • 05. Convolutional Neural Networks/11. Batch Normalization.mp4 13.7 MB
  • 13. Setting Up Your Environment (FAQ by Student Request)/1. Pre-Installation Check.mp4 13.7 MB
  • 10. In-Depth Loss Functions/2. Binary Cross Entropy.mp4 13.4 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/9. Python 2 vs Python 3.mp4 10.9 MB
  • 01. Welcome/3. How to Succeed in this Course.mp4 9.4 MB
  • 03. Machine Learning and Neurons/1. Review Section Introduction.mp4 7.9 MB
  • 01. Welcome/1. Introduction and Outline.mp4 7.8 MB
  • 01. Welcome/2. Where to get the code.mp4 7.1 MB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/7. How to Uncompress a .tar.gz file.mp4 6.7 MB
  • 04. Feedforward Artificial Neural Networks/7. Color Mixing Clarification.mp4 2.8 MB
  • 03. Machine Learning and Neurons/6. Regression Notebook.vtt 30.3 kB
  • 15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 29.0 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/5. How to Code by Yourself (part 1).vtt 28.5 kB
  • 05. Convolutional Neural Networks/6. CNN Architecture.vtt 25.7 kB
  • 06. Natural Language Processing (NLP)/5. Text Classification with CNNs.vtt 25.1 kB
  • 03. Machine Learning and Neurons/4. Classification Notebook.vtt 24.1 kB
  • 15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).vtt 21.4 kB
  • 06. Natural Language Processing (NLP)/3. Text Preprocessing.vtt 21.3 kB
  • 04. Feedforward Artificial Neural Networks/4. Activation Functions.vtt 20.4 kB
  • 05. Convolutional Neural Networks/4. Why use 0-indexing.vtt 20.2 kB
  • 05. Convolutional Neural Networks/5. Convolution on Color Images.vtt 18.8 kB
  • 08. Convolutional Neural Network Description/2. Tracking Shapes in a CNN.vtt 18.7 kB
  • 05. Convolutional Neural Networks/1. What is Convolution (part 1).vtt 18.6 kB
  • 03. Machine Learning and Neurons/3. Code Preparation (Classification Theory).vtt 18.6 kB
  • 05. Convolutional Neural Networks/7. CNN Code Preparation.vtt 18.1 kB
  • 13. Setting Up Your Environment (FAQ by Student Request)/2. Anaconda Environment Setup.vtt 17.7 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. Beginner's Coding Tips.vtt 17.2 kB
  • 13. Setting Up Your Environment (FAQ by Student Request)/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 17.2 kB
  • 03. Machine Learning and Neurons/2. What is Machine Learning.vtt 17.1 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/6. How to Code by Yourself (part 2).vtt 16.5 kB
  • 06. Natural Language Processing (NLP)/2. Code Preparation (NLP).vtt 16.5 kB
  • 06. Natural Language Processing (NLP)/1. Embeddings.vtt 15.8 kB
  • 11. In-Depth Gradient Descent/5. Adam (pt 1).vtt 15.2 kB
  • 15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).vtt 15.0 kB
  • 04. Feedforward Artificial Neural Networks/8. Code Preparation (ANN).vtt 14.8 kB
  • 04. Feedforward Artificial Neural Networks/6. How to Represent Images.vtt 14.4 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. How to use Github & Extra Coding Tips (Optional).vtt 14.1 kB
  • 11. In-Depth Gradient Descent/4. Variable and Adaptive Learning Rates.vtt 13.7 kB
  • 09. Practical Tips/1. Advanced CNNs and how to Design your Own.vtt 13.6 kB
  • 15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).vtt 13.4 kB
  • 02. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.vtt 13.0 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/8. Proof that using Jupyter Notebook is the same as not using it.vtt 13.0 kB
  • 02. Google Colab/3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.vtt 13.0 kB
  • 03. Machine Learning and Neurons/8. How does a model learn.vtt 12.9 kB
  • 08. Convolutional Neural Network Description/1. Convolution on 3-D Images.vtt 12.7 kB
  • 11. In-Depth Gradient Descent/6. Adam (pt 2).vtt 12.7 kB
  • 05. Convolutional Neural Networks/12. Improving CIFAR-10 Results (Legacy).vtt 12.1 kB
  • 04. Feedforward Artificial Neural Networks/10. ANN for Regression.vtt 12.0 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/10. Is Theano Dead.vtt 12.0 kB
  • 03. Machine Learning and Neurons/7. The Neuron.vtt 11.5 kB
  • 04. Feedforward Artificial Neural Networks/2. Forward Propagation.vtt 11.2 kB
  • 02. Google Colab/2. Uploading your own data to Google Colab.vtt 11.1 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. Get Your Hands Dirty, Practical Coding Experience, Data Links.vtt 10.8 kB
  • 04. Feedforward Artificial Neural Networks/3. The Geometrical Picture.vtt 10.7 kB
  • 10. In-Depth Loss Functions/1. Mean Squared Error.vtt 10.4 kB
  • 05. Convolutional Neural Networks/10. Data Augmentation.vtt 10.4 kB
  • 04. Feedforward Artificial Neural Networks/5. Multiclass Classification.vtt 10.1 kB
  • 04. Feedforward Artificial Neural Networks/9. ANN for Image Classification.vtt 9.2 kB
  • 06. Natural Language Processing (NLP)/4. CNNs for Text.vtt 9.1 kB
  • 11. In-Depth Gradient Descent/1. Gradient Descent.vtt 9.0 kB
  • 10. In-Depth Loss Functions/3. Categorical Cross Entropy.vtt 9.0 kB
  • 12. Appendix FAQ Intro/1. What is the Appendix.vtt 8.3 kB
  • 03. Machine Learning and Neurons/5. Code Preparation (Regression Theory).vtt 8.2 kB
  • 07. Convolution In-Depth/1. Real-Life Examples of Convolution.vtt 8.0 kB
  • 07. Convolution In-Depth/3. Alternative Views on Convolution.vtt 7.6 kB
  • 03. Machine Learning and Neurons/9. Making Predictions.vtt 7.5 kB
  • 05. Convolutional Neural Networks/8. CNN for Fashion MNIST.vtt 7.3 kB
  • 04. Feedforward Artificial Neural Networks/1. Artificial Neural Networks Section Introduction.vtt 7.2 kB
  • 16. Appendix FAQ Finale/1. BONUS.vtt 7.2 kB
  • 05. Convolutional Neural Networks/3. What is Convolution (part 3).vtt 7.2 kB
  • 07. Convolution In-Depth/2. Beginner's Guide to Convolution.vtt 7.2 kB
  • 11. In-Depth Gradient Descent/3. Momentum.vtt 7.0 kB
  • 10. In-Depth Loss Functions/2. Binary Cross Entropy.vtt 6.6 kB
  • 05. Convolutional Neural Networks/2. What is Convolution (part 2).vtt 6.5 kB
  • 05. Convolutional Neural Networks/11. Batch Normalization.vtt 6.1 kB
  • 01. Welcome/2. Where to get the code.vtt 6.1 kB
  • 13. Setting Up Your Environment (FAQ by Student Request)/1. Pre-Installation Check.vtt 5.9 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/9. Python 2 vs Python 3.vtt 5.6 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Where To Get the Code Troubleshooting.vtt 5.2 kB
  • 05. Convolutional Neural Networks/9. CNN for CIFAR-10.vtt 5.1 kB
  • 11. In-Depth Gradient Descent/2. Stochastic Gradient Descent.vtt 4.8 kB
  • 03. Machine Learning and Neurons/10. Saving and Loading a Model.vtt 4.5 kB
  • 03. Machine Learning and Neurons/11. Suggestion Box.vtt 4.2 kB
  • 01. Welcome/3. How to Succeed in this Course.vtt 4.0 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/7. How to Uncompress a .tar.gz file.vtt 3.7 kB
  • 01. Welcome/1. Introduction and Outline.vtt 3.3 kB
  • 03. Machine Learning and Neurons/1. Review Section Introduction.vtt 3.3 kB
  • 02. Google Colab/4. Temporary 403 Errors.vtt 3.3 kB
  • 04. Feedforward Artificial Neural Networks/7. Color Mixing Clarification.vtt 1.0 kB
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. Data-Links.txt 96 Bytes
  • 01. Welcome/2. Github-Link.txt 81 Bytes
  • 14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. Github-Link.txt 81 Bytes
  • 01. Welcome/2. Code-Link.txt 64 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！