589689.xyz

Learn Artificial Neural Network From Scratch in Python

  • 收录时间:2021-06-28 21:16:21
  • 文件大小:6GB
  • 下载次数:1
  • 最近下载:2021-06-28 21:16:21
  • 磁力链接:
立即下载 复制链接

文件列表

  1. 02 Optional but Recommended [Learn Python in Easy Way]/020 Classes and Objects in Python.mp4 277MB
  2. 03 Prerequisite_ ML libraries for data preprocessing/002 Data Preprocessing Part 1.mp4 229MB
  3. 02 Optional but Recommended [Learn Python in Easy Way]/012 Python _List_ Data Structures.mp4 194MB
  4. 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/002 Implementation of MLP classifier using scikit-learn.mp4 166MB
  5. 05 Tutorial_ Numerical on Backpropagation/005 Backpropagation in ANN.mp4 165MB
  6. 03 Prerequisite_ ML libraries for data preprocessing/006 Introduction to pandas module.mp4 164MB
  7. 03 Prerequisite_ ML libraries for data preprocessing/010 Cross entropy of Logistic Regression.mp4 158MB
  8. 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/001 Creating data sets on our own!!.mp4 157MB
  9. 03 Prerequisite_ ML libraries for data preprocessing/003 Data Preprocessing Part 2.mp4 155MB
  10. 03 Prerequisite_ ML libraries for data preprocessing/009 Introduction to overfit and underfit of model.mp4 141MB
  11. 08 Explore more_ Computational Neural Network [advanced]/001 Introduction to feed forward and backward propagation in computational graph.mp4 133MB
  12. 02 Optional but Recommended [Learn Python in Easy Way]/018 User Defined Functions in Python.mp4 130MB
  13. 05 Tutorial_ Numerical on Backpropagation/003 Forward Propagation of Artificial Neural Network.mp4 128MB
  14. 06 Workshop_ Coding Artificial Neural Network from Scratch/004 Coding dense layer [must know Object Oriented Programming].mp4 121MB
  15. 03 Prerequisite_ ML libraries for data preprocessing/004 Data Preprocessing Part 3.mp4 118MB
  16. 02 Optional but Recommended [Learn Python in Easy Way]/011 Built-in Modules and Creating your own Modules.mp4 117MB
  17. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/002 Introduction to Neural Networks.mp4 116MB
  18. 02 Optional but Recommended [Learn Python in Easy Way]/021 Basic Inheritance in Python.mp4 114MB
  19. 01 Introduction/004 Introduction to Jupyter Notebook.mp4 111MB
  20. 01 Introduction/005 Introduction to Artificial Intelligence and Machine Learning [lecture].mp4 110MB
  21. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/008 Introduction to the Activation Function.mp4 106MB
  22. 06 Workshop_ Coding Artificial Neural Network from Scratch/005 Introduction to Activation Function.mp4 105MB
  23. 02 Optional but Recommended [Learn Python in Easy Way]/008 Operators and Operands.mp4 104MB
  24. 06 Workshop_ Coding Artificial Neural Network from Scratch/002 Coding neuron layer.mp4 95MB
  25. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/006 Updating the weights [partial differentiation].mp4 92MB
  26. 03 Prerequisite_ ML libraries for data preprocessing/007 Train and Test Splitting of Data.mp4 89MB
  27. 02 Optional but Recommended [Learn Python in Easy Way]/006 Data Types_ String, Set and Numbers.mp4 86MB
  28. 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/004 Experimentation of hyper parameters.mp4 86MB
  29. 01 Introduction/003 Set up environment and Download Machine Learning Libraries.mp4 81MB
  30. 02 Optional but Recommended [Learn Python in Easy Way]/017 Looping in Python_ for Loops.mp4 79MB
  31. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/012 Introduction to Stochastic Gradient Descent and Adam Optimizer.mp4 78MB
  32. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/003 Inspiration and representation for Neural Network.mp4 77MB
  33. 05 Tutorial_ Numerical on Backpropagation/004 Error in the problem.mp4 76MB
  34. 03 Prerequisite_ ML libraries for data preprocessing/005 Introduction to numpy module.mp4 72MB
  35. 05 Tutorial_ Numerical on Backpropagation/001 Derivative of sigmoid function [must watch].mp4 70MB
  36. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/004 History and Application of Neural Network.mp4 70MB
  37. 06 Workshop_ Coding Artificial Neural Network from Scratch/006 Implementation of activation function [step and sigmoid].mp4 69MB
  38. 01 Introduction/002 Install anaconda on your machine.mp4 69MB
  39. 06 Workshop_ Coding Artificial Neural Network from Scratch/001 Setting up environment and coding single neuron.mp4 69MB
  40. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/001 Introduction to Artificial Intelligence.mp4 68MB
  41. 03 Prerequisite_ ML libraries for data preprocessing/008 Encoding Process in Machine Learning.mp4 68MB
  42. 02 Optional but Recommended [Learn Python in Easy Way]/007 Data Types_ List, Dictionaty and Tuple.mp4 68MB
  43. 02 Optional but Recommended [Learn Python in Easy Way]/010 Comments and User Input.mp4 66MB
  44. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/010 Why we use regularization in the Neural Network.mp4 63MB
  45. 02 Optional but Recommended [Learn Python in Easy Way]/013 Python _Dictionary_ Data Structures.mp4 63MB
  46. 06 Workshop_ Coding Artificial Neural Network from Scratch/007 Implementation of activation function [tanh and ReLu].mp4 62MB
  47. 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/003 Evaluation of the model (Neural Network).mp4 61MB
  48. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/011 Introduction to the gradient descent [review].mp4 61MB
  49. 02 Optional but Recommended [Learn Python in Easy Way]/005 Variables on Python.mp4 58MB
  50. 02 Optional but Recommended [Learn Python in Easy Way]/004 How to read Python documentation.mp4 58MB
  51. 02 Optional but Recommended [Learn Python in Easy Way]/003 Download and setup Pycharm code editon on Linux.mp4 57MB
  52. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/007 Introduction to partial differentiation.mp4 56MB
  53. 02 Optional but Recommended [Learn Python in Easy Way]/001 Download and setup Pycharm code editor on Windows.mp4 56MB
  54. 02 Optional but Recommended [Learn Python in Easy Way]/009 Logical Operators and Operations.mp4 53MB
  55. 02 Optional but Recommended [Learn Python in Easy Way]/015 Python Conditionals_ if...else statements.mp4 50MB
  56. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/005 Example of neural network.mp4 49MB
  57. 06 Workshop_ Coding Artificial Neural Network from Scratch/003 Using dot product to code neuron layer.mp4 49MB
  58. 02 Optional but Recommended [Learn Python in Easy Way]/022 Multiple Inheritance in Python.mp4 47MB
  59. 05 Tutorial_ Numerical on Backpropagation/002 Introduction to the problem.mp4 45MB
  60. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/009 Why do we need bias in the program.mp4 45MB
  61. 02 Optional but Recommended [Learn Python in Easy Way]/023 __name__ == __main__.mp4 42MB
  62. 02 Optional but Recommended [Learn Python in Easy Way]/014 Python Indentation.mp4 41MB
  63. 02 Optional but Recommended [Learn Python in Easy Way]/002 Download Visual Studio code editor on Windows (Optional).mp4 35MB
  64. 02 Optional but Recommended [Learn Python in Easy Way]/019 Default Arguments in Python.mp4 33MB
  65. 03 Prerequisite_ ML libraries for data preprocessing/001 Data Types in Machine Learning.mp4 32MB
  66. 02 Optional but Recommended [Learn Python in Easy Way]/016 Looping in Python_ while Loops.mp4 31MB
  67. 01 Introduction/001 Introduction.mp4 24MB
  68. 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/013 Introduction to mini-batch SGD.mp4 16MB
  69. 05 Tutorial_ Numerical on Backpropagation/052 A Step by Step Backpropagation.pdf 4MB
  70. 05 Tutorial_ Numerical on Backpropagation/053 A Step by Step Backpropagation.pdf 4MB
  71. 05 Tutorial_ Numerical on Backpropagation/054 A Step by Step Backpropagation.pdf 4MB
  72. 05 Tutorial_ Numerical on Backpropagation/056 A Step by Step Backpropagation.pdf 4MB
  73. 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/064 MLP workshop/MLP workshop.ipynb 1MB
  74. 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/065 MLP workshop/MLP workshop.ipynb 1MB
  75. 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/066 MLP workshop/MLP workshop.ipynb 1MB
  76. 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/067 MLP workshop/MLP workshop.ipynb 1MB
  77. 03 Prerequisite_ ML libraries for data preprocessing/038 Confusion Matrix for your Multi-Class ML Model.pdf 268KB
  78. 06 Workshop_ Coding Artificial Neural Network from Scratch/061 Activation function/Activation function.ipynb 72KB
  79. 06 Workshop_ Coding Artificial Neural Network from Scratch/062 Activation function/Activation function.ipynb 72KB
  80. 06 Workshop_ Coding Artificial Neural Network from Scratch/063 Activation function/Activation function.ipynb 72KB
  81. 06 Workshop_ Coding Artificial Neural Network from Scratch/057 Artificial NN from scratch/Artificial NN from scratch.ipynb 9KB
  82. 06 Workshop_ Coding Artificial Neural Network from Scratch/058 Artificial NN from scratch/Artificial NN from scratch.ipynb 9KB
  83. 06 Workshop_ Coding Artificial Neural Network from Scratch/059 Artificial NN from scratch/Artificial NN from scratch.ipynb 9KB
  84. Downloaded from 1337x.html 543B