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| 001 Creating data sets on our own!!.mp4 |
156.63Мб |
| 001 Data Types in Machine Learning.mp4 |
31.60Мб |
| 001 Derivative of sigmoid function [must watch].mp4 |
69.53Мб |
| 001 Download and setup Pycharm code editor on Windows.mp4 |
55.76Мб |
| 001 Introduction.mp4 |
24.27Мб |
| 001 Introduction to Artificial Intelligence.mp4 |
68.29Мб |
| 001 Introduction to feed forward and backward propagation in computational graph.mp4 |
132.76Мб |
| 001 Setting up environment and coding single neuron.mp4 |
68.80Мб |
| 002 Coding neuron layer.mp4 |
94.62Мб |
| 002 Data Preprocessing Part 1.mp4 |
229.04Мб |
| 002 Download Visual Studio code editor on Windows (Optional).mp4 |
34.88Мб |
| 002 Implementation of MLP classifier using scikit-learn.mp4 |
166.09Мб |
| 002 Install anaconda on your machine.mp4 |
69.08Мб |
| 002 Introduction to Neural Networks.mp4 |
116.39Мб |
| 002 Introduction to the problem.mp4 |
45.30Мб |
| 003 Data Preprocessing Part 2.mp4 |
154.97Мб |
| 003 Download and setup Pycharm code editon on Linux.mp4 |
57.24Мб |
| 003 Evaluation of the model (Neural Network).mp4 |
61.42Мб |
| 003 Forward Propagation of Artificial Neural Network.mp4 |
127.96Мб |
| 003 Inspiration and representation for Neural Network.mp4 |
77.08Мб |
| 003 Set up environment and Download Machine Learning Libraries.mp4 |
80.51Мб |
| 003 Using dot product to code neuron layer.mp4 |
49.09Мб |
| 004 Coding dense layer [must know Object Oriented Programming].mp4 |
121.30Мб |
| 004 Data Preprocessing Part 3.mp4 |
117.85Мб |
| 004 Error in the problem.mp4 |
75.73Мб |
| 004 Experimentation of hyper parameters.mp4 |
85.95Мб |
| 004 History and Application of Neural Network.mp4 |
69.51Мб |
| 004 How to read Python documentation.mp4 |
57.57Мб |
| 004 Introduction to Jupyter Notebook.mp4 |
111.41Мб |
| 005 Backpropagation in ANN.mp4 |
164.81Мб |
| 005 Example of neural network.mp4 |
49.37Мб |
| 005 Introduction to Activation Function.mp4 |
104.95Мб |
| 005 Introduction to Artificial Intelligence and Machine Learning [lecture].mp4 |
110.50Мб |
| 005 Introduction to numpy module.mp4 |
71.94Мб |
| 005 Variables on Python.mp4 |
57.83Мб |
| 006 Data Types_ String, Set and Numbers.mp4 |
86.04Мб |
| 006 Implementation of activation function [step and sigmoid].mp4 |
69.30Мб |
| 006 Introduction to pandas module.mp4 |
164.14Мб |
| 006 Updating the weights [partial differentiation].mp4 |
92.48Мб |
| 007 Data Types_ List, Dictionaty and Tuple.mp4 |
67.53Мб |
| 007 Implementation of activation function [tanh and ReLu].mp4 |
62.05Мб |
| 007 Introduction to partial differentiation.mp4 |
56.08Мб |
| 007 Train and Test Splitting of Data.mp4 |
89.48Мб |
| 008 Encoding Process in Machine Learning.mp4 |
68.02Мб |
| 008 Introduction to the Activation Function.mp4 |
105.58Мб |
| 008 Operators and Operands.mp4 |
104.45Мб |
| 009 Introduction to overfit and underfit of model.mp4 |
141.02Мб |
| 009 Logical Operators and Operations.mp4 |
53.06Мб |
| 009 Why do we need bias in the program.mp4 |
44.79Мб |
| 010 Comments and User Input.mp4 |
66.04Мб |
| 010 Cross entropy of Logistic Regression.mp4 |
157.88Мб |
| 010 Why we use regularization in the Neural Network.mp4 |
63.10Мб |
| 011 Built-in Modules and Creating your own Modules.mp4 |
117.16Мб |
| 011 Introduction to the gradient descent [review].mp4 |
60.52Мб |
| 012 Introduction to Stochastic Gradient Descent and Adam Optimizer.mp4 |
77.98Мб |
| 012 Python _List_ Data Structures.mp4 |
194.26Мб |
| 013 Introduction to mini-batch SGD.mp4 |
16.20Мб |
| 013 Python _Dictionary_ Data Structures.mp4 |
62.57Мб |
| 014 Python Indentation.mp4 |
41.15Мб |
| 015 Python Conditionals_ if...else statements.mp4 |
49.58Мб |
| 016 Looping in Python_ while Loops.mp4 |
31.40Мб |
| 017 Looping in Python_ for Loops.mp4 |
78.55Мб |
| 018 User Defined Functions in Python.mp4 |
130.34Мб |
| 019 Default Arguments in Python.mp4 |
33.04Мб |
| 020 Classes and Objects in Python.mp4 |
276.69Мб |
| 021 Basic Inheritance in Python.mp4 |
113.84Мб |
| 022 Multiple Inheritance in Python.mp4 |
47.46Мб |
| 023 __name__ == __main__.mp4 |
42.43Мб |
| 038 Confusion Matrix for your Multi-Class ML Model.pdf |
267.59Кб |
| 052 A Step by Step Backpropagation.pdf |
3.86Мб |
| 053 A Step by Step Backpropagation.pdf |
3.86Мб |
| 054 A Step by Step Backpropagation.pdf |
3.86Мб |
| 056 A Step by Step Backpropagation.pdf |
3.86Мб |
| Activation function.ipynb |
71.64Кб |
| Activation function.ipynb |
71.64Кб |
| Activation function.ipynb |
71.64Кб |
| Artificial NN from scratch.ipynb |
9.22Кб |
| Artificial NN from scratch.ipynb |
9.22Кб |
| Artificial NN from scratch.ipynb |
9.22Кб |
| Downloaded from 1337x.html |
543б |
| MLP workshop.ipynb |
1.43Мб |
| MLP workshop.ipynb |
1.43Мб |
| MLP workshop.ipynb |
1.43Мб |
| MLP workshop.ipynb |
1.43Мб |