首页 磁力链接怎么用

GetFreeCourses.Co-Udemy-Time Series Analysis, Forecasting, and Machine 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 2023-1-4 06:43 2024-12-29 14:01 228 4.84 GB 119
二维码链接
GetFreeCourses.Co-Udemy-Time Series Analysis, Forecasting, and Machine 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. 01 Welcome/001 Introduction and Outline.mp430.69MB
  2. 01 Welcome/002 Where to Get the Code.mp461.97MB
  3. 01 Welcome/003 Warmup (Optional).mp423.16MB
  4. 02 Time Series Basics/001 Time Series Basics Section Introduction.mp417.46MB
  5. 02 Time Series Basics/002 What is a Time Series_.mp432.24MB
  6. 02 Time Series Basics/003 Modeling vs. Predicting.mp413.48MB
  7. 02 Time Series Basics/004 Why Do We Care About Shapes_.mp429.48MB
  8. 02 Time Series Basics/005 Types of Tasks.mp423.55MB
  9. 02 Time Series Basics/006 Power, Log, and Box-Cox Transformations.mp432.63MB
  10. 02 Time Series Basics/007 Power, Log, and Box-Cox Transformations in Code.mp433.29MB
  11. 02 Time Series Basics/008 Forecasting Metrics.mp443.71MB
  12. 02 Time Series Basics/009 Financial Time Series Primer.mp444.86MB
  13. 02 Time Series Basics/010 Price Simulations in Code.mp418.28MB
  14. 02 Time Series Basics/011 Random Walks and the Random Walk Hypothesis.mp468.11MB
  15. 02 Time Series Basics/012 The Naive Forecast and the Importance of Baselines.mp430.11MB
  16. 02 Time Series Basics/013 Naive Forecast and Forecasting Metrics in Code.mp441.47MB
  17. 02 Time Series Basics/014 Time Series Basics Section Summary.mp412.13MB
  18. 02 Time Series Basics/015 Suggestion Box.mp416.12MB
  19. 03 Exponential Smoothing and ETS Methods/001 Exponential Smoothing Section Introduction.mp413.56MB
  20. 03 Exponential Smoothing and ETS Methods/002 Exponential Smoothing Intuition for Beginners.mp423.91MB
  21. 03 Exponential Smoothing and ETS Methods/003 SMA Theory.mp415.24MB
  22. 03 Exponential Smoothing and ETS Methods/004 SMA Code.mp453.57MB
  23. 03 Exponential Smoothing and ETS Methods/005 EWMA Theory.mp435.83MB
  24. 03 Exponential Smoothing and ETS Methods/006 EWMA Code.mp439.41MB
  25. 03 Exponential Smoothing and ETS Methods/007 SES Theory.mp435.57MB
  26. 03 Exponential Smoothing and ETS Methods/008 SES Code.mp469.54MB
  27. 03 Exponential Smoothing and ETS Methods/009 Holt's Linear Trend Model (Theory).mp433.2MB
  28. 03 Exponential Smoothing and ETS Methods/010 Holt's Linear Trend Model (Code).mp419.05MB
  29. 03 Exponential Smoothing and ETS Methods/011 Holt-Winters (Theory).mp447.55MB
  30. 03 Exponential Smoothing and ETS Methods/012 Holt-Winters (Code).mp449.8MB
  31. 03 Exponential Smoothing and ETS Methods/013 Walk-Forward Validation.mp444.31MB
  32. 03 Exponential Smoothing and ETS Methods/014 Walk-Forward Validation in Code.mp460.25MB
  33. 03 Exponential Smoothing and ETS Methods/015 Application_ Sales Data.mp429.44MB
  34. 03 Exponential Smoothing and ETS Methods/016 Application_ Stock Predictions.mp440.51MB
  35. 03 Exponential Smoothing and ETS Methods/017 SMA Application_ COVID-19 Counting.mp419.37MB
  36. 03 Exponential Smoothing and ETS Methods/018 SMA Application_ Algorithmic Trading.mp411.59MB
  37. 03 Exponential Smoothing and ETS Methods/019 Exponential Smoothing Section Summary.mp419.12MB
  38. 04 ARIMA/001 ARIMA Section Introduction.mp423.01MB
  39. 04 ARIMA/002 Autoregressive Models - AR(p).mp452.54MB
  40. 04 ARIMA/003 Moving Average Models - MA(q).mp410.13MB
  41. 04 ARIMA/004 ARIMA.mp441.39MB
  42. 04 ARIMA/005 ARIMA in Code.mp4121.58MB
  43. 04 ARIMA/006 Stationarity.mp455.15MB
  44. 04 ARIMA/007 Stationarity in Code.mp461.5MB
  45. 04 ARIMA/008 ACF (Autocorrelation Function).mp437MB
  46. 04 ARIMA/009 PACF (Partial Autocorrelation Funtion).mp425.11MB
  47. 04 ARIMA/010 ACF and PACF in Code (pt 1).mp441.31MB
  48. 04 ARIMA/011 ACF and PACF in Code (pt 2).mp433.88MB
  49. 04 ARIMA/012 Auto ARIMA and SARIMAX.mp439.45MB
  50. 04 ARIMA/013 Model Selection, AIC and BIC.mp445.91MB
  51. 04 ARIMA/014 Auto ARIMA in Code.mp4103.19MB
  52. 04 ARIMA/015 Auto ARIMA in Code (Stocks).mp4105.21MB
  53. 04 ARIMA/016 ACF and PACF for Stock Returns.mp443.5MB
  54. 04 ARIMA/017 Auto ARIMA in Code (Sales Data).mp465.42MB
  55. 04 ARIMA/018 How to Forecast with ARIMA.mp437.95MB
  56. 04 ARIMA/019 ARIMA Section Summary.mp412.74MB
  57. 05 Machine Learning Methods/001 Machine Learning Section Introduction.mp417.53MB
  58. 05 Machine Learning Methods/002 Supervised Machine Learning_ Classification and Regression.mp468.96MB
  59. 05 Machine Learning Methods/003 Autoregressive Machine Learning Models.mp432.38MB
  60. 05 Machine Learning Methods/004 Machine Learning Algorithms_ Linear Regression.mp421.8MB
  61. 05 Machine Learning Methods/005 Machine Learning Algorithms_ Logistic Regression.mp431.74MB
  62. 05 Machine Learning Methods/006 Machine Learning Algorithms_ Support Vector Machines.mp443.52MB
  63. 05 Machine Learning Methods/007 Machine Learning Algorithms_ Random Forest.mp432.02MB
  64. 05 Machine Learning Methods/008 Extrapolation and Stock Prices.mp464.73MB
  65. 05 Machine Learning Methods/009 Machine Learning for Time Series Forecasting in Code (pt 1).mp486.17MB
  66. 05 Machine Learning Methods/010 Forecasting with Differencing.mp418.97MB
  67. 05 Machine Learning Methods/011 Machine Learning for Time Series Forecasting in Code (pt 2).mp449.4MB
  68. 05 Machine Learning Methods/012 Application_ Sales Data.mp442.19MB
  69. 05 Machine Learning Methods/013 Application_ Predicting Stock Prices and Returns.mp437.36MB
  70. 05 Machine Learning Methods/014 Application_ Predicting Stock Movements.mp426.28MB
  71. 05 Machine Learning Methods/015 Machine Learning Section Summary.mp410.36MB
  72. 06 Deep Learning_ Artificial Neural Networks (ANN)/001 Artificial Neural Networks_ Section Introduction.mp419.43MB
  73. 06 Deep Learning_ Artificial Neural Networks (ANN)/002 The Neuron.mp443.86MB
  74. 06 Deep Learning_ Artificial Neural Networks (ANN)/003 Forward Propagation.mp444.79MB
  75. 06 Deep Learning_ Artificial Neural Networks (ANN)/004 The Geometrical Picture.mp453.97MB
  76. 06 Deep Learning_ Artificial Neural Networks (ANN)/005 Activation Functions.mp486.54MB
  77. 06 Deep Learning_ Artificial Neural Networks (ANN)/006 Multiclass Classification.mp443.63MB
  78. 06 Deep Learning_ Artificial Neural Networks (ANN)/007 ANN Code Preparation.mp457.51MB
  79. 06 Deep Learning_ Artificial Neural Networks (ANN)/008 Feedforward ANN for Time Series Forecasting Code.mp470.91MB
  80. 06 Deep Learning_ Artificial Neural Networks (ANN)/009 Feedforward ANN for Stock Return and Price Predictions Code.mp467.71MB
  81. 06 Deep Learning_ Artificial Neural Networks (ANN)/010 Human Activity Recognition Dataset.mp430.74MB
  82. 06 Deep Learning_ Artificial Neural Networks (ANN)/011 Human Activity Recognition_ Code Preparation.mp431.27MB
  83. 06 Deep Learning_ Artificial Neural Networks (ANN)/012 Human Activity Recognition_ Data Exploration.mp449.95MB
  84. 06 Deep Learning_ Artificial Neural Networks (ANN)/013 Human Activity Recognition_ Multi-Input ANN.mp467.55MB
  85. 06 Deep Learning_ Artificial Neural Networks (ANN)/014 Human Activity Recognition_ Feature-Based Model.mp436.06MB
  86. 06 Deep Learning_ Artificial Neural Networks (ANN)/015 Human Activity Recognition_ Combined Model.mp420.9MB
  87. 06 Deep Learning_ Artificial Neural Networks (ANN)/016 How Does a Neural Network _Learn__.mp450.07MB
  88. 06 Deep Learning_ Artificial Neural Networks (ANN)/017 Artificial Neural Networks_ Section Summary.mp410.95MB
  89. 07 Deep Learning_ Convolutional Neural Networks (CNN)/001 CNN Section Introduction.mp414.31MB
  90. 07 Deep Learning_ Convolutional Neural Networks (CNN)/002 What is Convolution_.mp478.29MB
  91. 07 Deep Learning_ Convolutional Neural Networks (CNN)/003 What is Convolution_ (Pattern-Matching).mp423.69MB
  92. 07 Deep Learning_ Convolutional Neural Networks (CNN)/004 What is Convolution_ (Weight Sharing).mp430.44MB
  93. 07 Deep Learning_ Convolutional Neural Networks (CNN)/005 Convolution on Color Images.mp473.99MB
  94. 07 Deep Learning_ Convolutional Neural Networks (CNN)/006 Convolution for Time Series and ARIMA.mp423.61MB
  95. 07 Deep Learning_ Convolutional Neural Networks (CNN)/007 CNN Architecture.mp496.82MB
  96. 07 Deep Learning_ Convolutional Neural Networks (CNN)/008 CNN Code Preparation.mp427.49MB
  97. 07 Deep Learning_ Convolutional Neural Networks (CNN)/009 CNN for Time Series Forecasting in Code.mp448.78MB
  98. 07 Deep Learning_ Convolutional Neural Networks (CNN)/010 CNN for Human Activity Recognition.mp446.39MB
  99. 07 Deep Learning_ Convolutional Neural Networks (CNN)/011 CNN Section Summary.mp415.43MB
  100. 08 VIP_ AWS Forecast/001 AWS Forecast Section Introduction.mp443.54MB
  101. 08 VIP_ AWS Forecast/002 Data Model.mp448.96MB
  102. 08 VIP_ AWS Forecast/003 Creating an IAM Role.mp423.8MB
  103. 08 VIP_ AWS Forecast/004 Code pt 1 (Getting and Transforming the Data).mp463.34MB
  104. 08 VIP_ AWS Forecast/005 Code pt 2 (Uploading the data to S3).mp491.06MB
  105. 08 VIP_ AWS Forecast/006 Code pt 3 (Building your Model).mp454.47MB
  106. 08 VIP_ AWS Forecast/007 Code pt 4 (Generating and Evaluating the Forecast).mp449.88MB
  107. 08 VIP_ AWS Forecast/008 AWS Forecast Exercise.mp413.76MB
  108. 08 VIP_ AWS Forecast/009 AWS Forecast Section Summary.mp425.46MB
  109. 10 Setting Up Your Environment FAQ/001 Anaconda Environment Setup.mp427.88MB
  110. 10 Setting Up Your Environment FAQ/002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.61MB
  111. 11 Extra Help With Python Coding for Beginners FAQ/001 How to Code by Yourself (part 1).mp424.59MB
  112. 11 Extra Help With Python Coding for Beginners FAQ/002 How to Code by Yourself (part 2).mp449.18MB
  113. 11 Extra Help With Python Coding for Beginners FAQ/003 Proof that using Jupyter Notebook is the same as not using it.mp469.51MB
  114. 12 Effective Learning Strategies for Machine Learning FAQ/001 How to Succeed in this Course (Long Version).mp412.6MB
  115. 12 Effective Learning Strategies for Machine Learning FAQ/002 Is this for Beginners or Experts_ Academic or Practical_ Fast or slow-paced_.mp438.95MB
  116. 12 Effective Learning Strategies for Machine Learning FAQ/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp479.62MB
  117. 12 Effective Learning Strategies for Machine Learning FAQ/004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4108.19MB
  118. 13 Appendix _ FAQ Finale/001 What is the Appendix_.mp416.4MB
  119. 13 Appendix _ FAQ Finale/002 BONUS_ Where to get discount coupons and FREE deep learning material.mp437.81MB
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