首页 磁力链接怎么用

[DesireCourse.Net] Udemy - Tensorflow and Keras For Neural Networks and Deep Learning

文件类型 收录时间 最后活跃 资源热度 文件大小 文件数量
视频 2019-6-29 04:49 2024-11-16 16:54 236 4.33 GB 74
二维码链接
[DesireCourse.Net] Udemy - Tensorflow and Keras For Neural Networks and Deep Learning的二维码
种子下载(838888不存储任何种子文件)
种子下载线路1(迅雷)--推荐
种子下载线路2(比特彗星)
种子下载线路3(torcache)
3条线路均为国内外知名下载网站种子链接,内容跟本站无关!
文件列表
  1. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/1. Introduction to the Course.mp49.87MB
  2. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/3. Python Data Science Environment.mp494.25MB
  3. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/4. For Mac Users.mp450.18MB
  4. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/5. Introduction to IPython.mp4101MB
  5. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/6. Install Tensorflow.mp4167.82MB
  6. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/8. Install Keras on Windows 10.mp482.92MB
  7. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/9. Install Keras on Mac.mp477.09MB
  8. 10. Convolution Neural Network (CNN) For Image Analysis/1. Introduction to CNN.mp4183.49MB
  9. 10. Convolution Neural Network (CNN) For Image Analysis/10. CNN With Keras.mp437.8MB
  10. 10. Convolution Neural Network (CNN) For Image Analysis/11. CNN on Image Data with Keras-Part 1.mp424.4MB
  11. 10. Convolution Neural Network (CNN) For Image Analysis/12. CNN on Image Data with Keras-Part 2.mp440.73MB
  12. 10. Convolution Neural Network (CNN) For Image Analysis/2. Implement a CNN for Multi-Class Supervised Classification.mp479.45MB
  13. 10. Convolution Neural Network (CNN) For Image Analysis/3. Activation Functions.mp491.28MB
  14. 10. Convolution Neural Network (CNN) For Image Analysis/4. More on CNN.mp448.08MB
  15. 10. Convolution Neural Network (CNN) For Image Analysis/5. Pre-Requisite For Working With Imagery Data.mp420.06MB
  16. 10. Convolution Neural Network (CNN) For Image Analysis/6. CNN on Image Data-Part 1.mp4108.91MB
  17. 10. Convolution Neural Network (CNN) For Image Analysis/7. CNN on Image Data-Part 2.mp471.1MB
  18. 10. Convolution Neural Network (CNN) For Image Analysis/8. More on TFLearn.mp474.39MB
  19. 10. Convolution Neural Network (CNN) For Image Analysis/9. CNN Workflow for Keras.mp436.25MB
  20. 11. Autoencoders With Convolution Neural Networks (CNN)/1. Autoencoders for With CNN- Tensorflow.mp466.25MB
  21. 11. Autoencoders With Convolution Neural Networks (CNN)/2. Autoencoders for With CNN- Keras.mp441.12MB
  22. 12. Recurrent Neural Networks (RNN)/1. Theory Behind RNNs.mp457.21MB
  23. 12. Recurrent Neural Networks (RNN)/2. LSTM For Time Series Data.mp452.35MB
  24. 12. Recurrent Neural Networks (RNN)/3. LSTM for Predicting Stock Prices.mp472.32MB
  25. 13. Miscellaneous Section/1. Use Colabs for Jupyter Data Science.mp443.92MB
  26. 2. Introduction to Python Data Science Packages/1. Python Packages for Data Science.mp436.42MB
  27. 2. Introduction to Python Data Science Packages/2. Introduction to Numpy.mp431.19MB
  28. 2. Introduction to Python Data Science Packages/3. Create Numpy Arrays.mp463.3MB
  29. 2. Introduction to Python Data Science Packages/4. Numpy Operations.mp4111.82MB
  30. 2. Introduction to Python Data Science Packages/5. Numpy for Statistical Operation.mp447.83MB
  31. 2. Introduction to Python Data Science Packages/6. Introduction to Pandas.mp484.65MB
  32. 2. Introduction to Python Data Science Packages/7. Read in Data from CSV.mp453.72MB
  33. 2. Introduction to Python Data Science Packages/8. Read in Data from Excel.mp442.34MB
  34. 2. Introduction to Python Data Science Packages/9. Basic Data Cleaning.mp437.53MB
  35. 3. Introduction to TensorFlow/1. A Brief Touchdown.mp421.1MB
  36. 3. Introduction to TensorFlow/2. A Brief Touchdown Computational Graphs.mp411.25MB
  37. 3. Introduction to TensorFlow/4. A Tensorflow Session.mp428.3MB
  38. 3. Introduction to TensorFlow/5. Interactive Tensorflow Session.mp411.28MB
  39. 3. Introduction to TensorFlow/6. Constants and Variables in Tensorflow.mp425.87MB
  40. 3. Introduction to TensorFlow/7. Placeholders in Tensorflow.mp431.46MB
  41. 4. Introduction to Keras/1. What is Keras.mp423.92MB
  42. 5. Some Preliminary Tensorflow and Keras Applications/1. Theory of Linear Regression (OLS).mp4112.72MB
  43. 5. Some Preliminary Tensorflow and Keras Applications/10. Accuracy Assessment For Binary Classification.mp462.96MB
  44. 5. Some Preliminary Tensorflow and Keras Applications/11. Linear Classification with Binary Classification With Mixed Predictors.mp488.84MB
  45. 5. Some Preliminary Tensorflow and Keras Applications/12. Softmax Classification With Tensorflow.mp469.98MB
  46. 5. Some Preliminary Tensorflow and Keras Applications/2. OLS From First Principles.mp474.98MB
  47. 5. Some Preliminary Tensorflow and Keras Applications/3. Visualize the Results of OLS.mp426.53MB
  48. 5. Some Preliminary Tensorflow and Keras Applications/4. Multiple Regression With Tensorflow-Part 1.mp446.44MB
  49. 5. Some Preliminary Tensorflow and Keras Applications/5. Estimate With Tensorflow Estimators.mp411.55MB
  50. 5. Some Preliminary Tensorflow and Keras Applications/6. Multiple Regression With Tensorflow Estimators.mp458.76MB
  51. 5. Some Preliminary Tensorflow and Keras Applications/7. More on Linear Regressor Estimator.mp498.57MB
  52. 5. Some Preliminary Tensorflow and Keras Applications/8. GLM Generalized Linear Model.mp445.97MB
  53. 5. Some Preliminary Tensorflow and Keras Applications/9. Linear Classifier For Binary Classification.mp4107.26MB
  54. 6. Some Basic Concepts/1. What is Machine Learning.mp491.35MB
  55. 6. Some Basic Concepts/2. Theory Behind ANN (Artificial Neural Network) and DNN (Deep Neural Networks).mp4107.02MB
  56. 7. Unsupervised Learning With Tensorflow and Keras/1. What is Unsupervised Learning.mp430.6MB
  57. 7. Unsupervised Learning With Tensorflow and Keras/2. Autoencoders for Unsupervised Classification.mp421.16MB
  58. 7. Unsupervised Learning With Tensorflow and Keras/3. Autoencoders in Tensorflow (Binary Class Problem).mp470.56MB
  59. 7. Unsupervised Learning With Tensorflow and Keras/4. Autoencoders in Tensorflow (Multiple Classes).mp456.49MB
  60. 7. Unsupervised Learning With Tensorflow and Keras/5. Autoencoders in Keras (Simple).mp453.18MB
  61. 7. Unsupervised Learning With Tensorflow and Keras/6. Autoencoders in Keras (Sparsity Constraints).mp437.71MB
  62. 7. Unsupervised Learning With Tensorflow and Keras/7. Deep Autoencoder With Keras.mp468.09MB
  63. 8. Neural Network for Tensorflow & Keras/1. Multi Layer Perceptron (MLP) with Tensorflow.mp461.32MB
  64. 8. Neural Network for Tensorflow & Keras/2. Multi Layer Perceptron (MLP) With Keras.mp432.19MB
  65. 8. Neural Network for Tensorflow & Keras/3. Keras MLP For Binary Classification.mp436.73MB
  66. 8. Neural Network for Tensorflow & Keras/4. Keras MLP for Multiclass Classification.mp450.62MB
  67. 8. Neural Network for Tensorflow & Keras/5. Keras MLP for Regression.mp430.36MB
  68. 9. Deep Learning For Tensorflow & Keras/1. What is Artificial Intelligence.mp499.53MB
  69. 9. Deep Learning For Tensorflow & Keras/2. Deep Neural Network (DNN) Classifier With Tensorflow.mp462.68MB
  70. 9. Deep Learning For Tensorflow & Keras/3. Deep Neural Network (DNN) Classifier With Mixed Predictors.mp483.75MB
  71. 9. Deep Learning For Tensorflow & Keras/4. Deep Neural Network (DNN) Regression With Tensorflow.mp451.18MB
  72. 9. Deep Learning For Tensorflow & Keras/5. Wide & Deep Learning (Tensorflow).mp4122.9MB
  73. 9. Deep Learning For Tensorflow & Keras/6. DNN Classifier With Keras.mp430MB
  74. 9. Deep Learning For Tensorflow & Keras/7. DNN Classifier With Keras-Example 2.mp442.43MB
友情提示
不会用的朋友看这里 把磁力链接复制到离线下载,或者bt下载软件里即可下载文件,或者直接复制迅雷链接到迅雷里下载! 亲,你造吗?将网页分享给您的基友,下载的人越多速度越快哦!

违规内容投诉邮箱:[email protected]

概述 838888磁力搜索是一个磁力链接搜索引擎,是学术研究的副产品,用于解决资源过度分散的问题 它通过BitTorrent协议加入DHT网络,实时的自动采集数据,仅存储文件的标题、大小、文件列表、文件标识符(磁力链接)等基础信息 838888磁力搜索不下载任何真实资源,无法判断资源的合法性及真实性,使用838888磁力搜索服务的用户需自行鉴别内容的真伪 838888磁力搜索不上传任何资源,不提供Tracker服务,不提供种子文件的下载,这意味着838888磁力搜索 838888磁力搜索是一个完全合法的系统