Learn Artificial Neural Network From Scratch in Python

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Learn Artificial Neural Network From Scratch in Python

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文件大小： 5.91G
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收录时间：2022-04-03
最近下载：2024-12-11

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文件列表

  • 02 Optional but Recommended [Learn Python in Easy Way]/020 Classes and Objects in Python.mp4 290.1 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/002 Data Preprocessing Part 1.mp4 240.2 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/012 Python _List_ Data Structures.mp4 203.7 MB
  • 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/002 Implementation of MLP classifier using scikit-learn.mp4 174.2 MB
  • 05 Tutorial_ Numerical on Backpropagation/005 Backpropagation in ANN.mp4 172.8 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/006 Introduction to pandas module.mp4 172.1 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/010 Cross entropy of Logistic Regression.mp4 165.5 MB
  • 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/001 Creating data sets on our own!!.mp4 164.2 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/003 Data Preprocessing Part 2.mp4 162.5 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/009 Introduction to overfit and underfit of model.mp4 147.9 MB
  • 08 Explore more_ Computational Neural Network [advanced]/001 Introduction to feed forward and backward propagation in computational graph.mp4 139.2 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/018 User Defined Functions in Python.mp4 136.7 MB
  • 05 Tutorial_ Numerical on Backpropagation/003 Forward Propagation of Artificial Neural Network.mp4 134.2 MB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/004 Coding dense layer [must know Object Oriented Programming].mp4 127.2 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/004 Data Preprocessing Part 3.mp4 123.6 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/011 Built-in Modules and Creating your own Modules.mp4 122.9 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/002 Introduction to Neural Networks.mp4 122.0 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/021 Basic Inheritance in Python.mp4 119.4 MB
  • 01 Introduction/004 Introduction to Jupyter Notebook.mp4 116.8 MB
  • 01 Introduction/005 Introduction to Artificial Intelligence and Machine Learning [lecture].mp4 115.9 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/008 Introduction to the Activation Function.mp4 110.7 MB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/005 Introduction to Activation Function.mp4 110.0 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/008 Operators and Operands.mp4 109.5 MB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/002 Coding neuron layer.mp4 99.2 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/006 Updating the weights [partial differentiation].mp4 97.0 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/007 Train and Test Splitting of Data.mp4 93.8 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/006 Data Types_ String, Set and Numbers.mp4 90.2 MB
  • 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/004 Experimentation of hyper parameters.mp4 90.1 MB
  • 01 Introduction/003 Set up environment and Download Machine Learning Libraries.mp4 84.4 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/017 Looping in Python_ for Loops.mp4 82.4 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/012 Introduction to Stochastic Gradient Descent and Adam Optimizer.mp4 81.8 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/003 Inspiration and representation for Neural Network.mp4 80.8 MB
  • 05 Tutorial_ Numerical on Backpropagation/004 Error in the problem.mp4 79.4 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/005 Introduction to numpy module.mp4 75.4 MB
  • 05 Tutorial_ Numerical on Backpropagation/001 Derivative of sigmoid function [must watch].mp4 72.9 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/004 History and Application of Neural Network.mp4 72.9 MB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/006 Implementation of activation function [step and sigmoid].mp4 72.7 MB
  • 01 Introduction/002 Install anaconda on your machine.mp4 72.4 MB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/001 Setting up environment and coding single neuron.mp4 72.1 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/001 Introduction to Artificial Intelligence.mp4 71.6 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/008 Encoding Process in Machine Learning.mp4 71.3 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/007 Data Types_ List, Dictionaty and Tuple.mp4 70.8 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/010 Comments and User Input.mp4 69.2 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/010 Why we use regularization in the Neural Network.mp4 66.2 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/013 Python _Dictionary_ Data Structures.mp4 65.6 MB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/007 Implementation of activation function [tanh and ReLu].mp4 65.1 MB
  • 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/003 Evaluation of the model (Neural Network).mp4 64.4 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/011 Introduction to the gradient descent [review].mp4 63.5 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/005 Variables on Python.mp4 60.6 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/004 How to read Python documentation.mp4 60.4 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/003 Download and setup Pycharm code editon on Linux.mp4 60.0 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/007 Introduction to partial differentiation.mp4 58.8 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/001 Download and setup Pycharm code editor on Windows.mp4 58.5 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/009 Logical Operators and Operations.mp4 55.6 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/015 Python Conditionals_ if...else statements.mp4 52.0 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/005 Example of neural network.mp4 51.8 MB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/003 Using dot product to code neuron layer.mp4 51.5 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/022 Multiple Inheritance in Python.mp4 49.8 MB
  • 05 Tutorial_ Numerical on Backpropagation/002 Introduction to the problem.mp4 47.5 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/009 Why do we need bias in the program.mp4 47.0 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/023 __name__ == __main__.mp4 44.5 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/014 Python Indentation.mp4 43.2 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/002 Download Visual Studio code editor on Windows (Optional).mp4 36.6 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/019 Default Arguments in Python.mp4 34.6 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/001 Data Types in Machine Learning.mp4 33.1 MB
  • 02 Optional but Recommended [Learn Python in Easy Way]/016 Looping in Python_ while Loops.mp4 32.9 MB
  • 01 Introduction/001 Introduction.mp4 25.5 MB
  • 04 Lecture_ Introduction to neural networks --Mandatory (Don't miss out)/013 Introduction to mini-batch SGD.mp4 17.0 MB
  • 05 Tutorial_ Numerical on Backpropagation/052 A Step by Step Backpropagation.pdf 4.1 MB
  • 05 Tutorial_ Numerical on Backpropagation/053 A Step by Step Backpropagation.pdf 4.1 MB
  • 05 Tutorial_ Numerical on Backpropagation/054 A Step by Step Backpropagation.pdf 4.1 MB
  • 05 Tutorial_ Numerical on Backpropagation/056 A Step by Step Backpropagation.pdf 4.1 MB
  • 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/064 MLP workshop/MLP workshop.ipynb 1.5 MB
  • 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/065 MLP workshop/MLP workshop.ipynb 1.5 MB
  • 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/066 MLP workshop/MLP workshop.ipynb 1.5 MB
  • 07 Workshop_ Coding Multi Layer Perception (MLP) Classifier/067 MLP workshop/MLP workshop.ipynb 1.5 MB
  • 03 Prerequisite_ ML libraries for data preprocessing/038 Confusion Matrix for your Multi-Class ML Model.pdf 274.0 kB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/061 Activation function/Activation function.ipynb 73.4 kB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/062 Activation function/Activation function.ipynb 73.4 kB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/063 Activation function/Activation function.ipynb 73.4 kB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/057 Artificial NN from scratch/Artificial NN from scratch.ipynb 9.4 kB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/058 Artificial NN from scratch/Artificial NN from scratch.ipynb 9.4 kB
  • 06 Workshop_ Coding Artificial Neural Network from Scratch/059 Artificial NN from scratch/Artificial NN from scratch.ipynb 9.4 kB
  • Downloaded from 1337x.html 543 Bytes

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