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Название [FreeCoursesOnline.Me] PacktPub - Deep Learning with Real World Projects [Video]
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Activation Functions.mp4 151.30Мб
Activation Functions.mp4 41.88Мб
AlexNet.mp4 73.82Мб
Analysis - Part 1.mp4 109.77Мб
Analysis - Part 2.mp4 46.01Мб
Applications for CNN.mp4 54.50Мб
Architecture.mp4 22.48Мб
Assumptions in Neural Networks.mp4 45.80Мб
Back Propagation Training - Part 1.mp4 46.54Мб
Back Propagation Training - Part 10.mp4 23.04Мб
Back Propagation Training - Part 2.mp4 38.07Мб
Back Propagation Training - Part 3.mp4 14.74Мб
Back Propagation Training - Part 4.mp4 34.74Мб
Back Propagation Training - Part 5.mp4 34.76Мб
Back Propagation Training - Part 6.mp4 23.30Мб
Back Propagation Training - Part 7.mp4 20.59Мб
Back Propagation Training - Part 8.mp4 27.00Мб
Back Propagation Training - Part 9.mp4 28.96Мб
Batch data.mp4 8.52Мб
Batch Normalisation - Part 1.mp4 36.08Мб
Batch Normalisation - Part 2.mp4 37.55Мб
Batch Normalisation - Part 3.mp4 50.64Мб
Bidirectional RNN.mp4 14.31Мб
Bidirectional RNN.mp4 43.49Мб
Case Study - Part 1.mp4 194.08Мб
Case Study - Part 2.mp4 95.90Мб
Case Study - Part 3.mp4 39.14Мб
Code Password.mp4 719.85Кб
Combining Network.mp4 53.18Мб
Convolution - Part 1.mp4 43.40Мб
Convolution - Part 2.mp4 79.49Мб
Deep Learning.mp4 28.97Мб
Dropouts Part 1.mp4 24.18Мб
Dropouts Part 2.mp4 13.46Мб
Example for Perceptron.mp4 44.98Мб
Feature Map.mp4 127.57Мб
Finding Global Minima.mp4 10.31Мб
Formulas.mp4 18.56Мб
Gated Recurrent Network (GRU).mp4 27.03Мб
GoogleNet.mp4 48.70Мб
History of Deep learning.mp4 81.44Мб
Homogeneous Co-ordinate.mp4 23.61Мб
How you can help our Group!.txt 208б
Idea behind CNN - Part 1.mp4 45.92Мб
Idea behind CNN - Part 2.mp4 75.88Мб
Images.mp4 161.11Мб
Input Layer.mp4 53.57Мб
Introducing Keras.mp4 122.91Мб
Introducing Loss Function.mp4 44.13Мб
Introducing TensorFlow.mp4 45.42Мб
Introduction.mp4 65.60Мб
Introduction.mp4 10.86Мб
Introduction.mp4 4.43Мб
Introduction.mp4 23.91Мб
Introduction.mp4 50.45Мб
Introduction.mp4 35.37Мб
Introduction.mp4 42.93Мб
Introduction.mp4 7.73Мб
Introduction.mp4 44.61Мб
Introduction.mp4 19.69Мб
Introduction to Regularisation.mp4 49.04Мб
Introduction to RNN.mp4 13.47Мб
LSTM Equation.mp4 8.51Мб
LSTM - Part 1.mp4 7.66Мб
LSTM - Part 2.mp4 5.96Мб
LSTM - Part 3.mp4 4.17Мб
LSTM - Part 4.mp4 11.56Мб
LSTM - Part 5.mp4 19.68Мб
Multi Classifier.mp4 37.87Мб
Multi-Level Perceptrons.mp4 81.52Мб
Neural Network Playground.mp4 152.12Мб
Neural Networks.mp4 49.32Мб
One-to-Many.mp4 17.41Мб
Online Offline Mode.mp4 10.25Мб
Online Offline Mode.mp4 36.04Мб
Output Layer.mp4 14.07Мб
Padding.mp4 15.13Мб
Part-Of-Speech Tagger case-study (Part-1).mp4 56.18Мб
Part-Of-Speech Tagger case- study (Part-2).mp4 87.66Мб
Part-Of-Speech Tagger case- study (Part-3).mp4 42.59Мб
Part-Of-Speech Tagger case- study (Part-4).mp4 57.08Мб
Part-Of-Speech Tagger case- study (Part-5).mp4 109.35Мб
Part-Of-Speech Tagger case- study (Part-6).mp4 25.65Мб
Part-Of-Speech Tagger case- study (Part-7).mp4 59.99Мб
Part-Of-Speech Tagger case- study (Part-8).mp4 120.05Мб
Part-Of-Speech Tagger case- study (Part-9).mp4 30.86Мб
Perceptron.mp4 29.65Мб
Perceptron for Classifiers.mp4 31.96Мб
Perceptron in Depth.mp4 30.71Мб
Perceptrons.mp4 37.66Мб
Pooling.mp4 70.59Мб
Practical on CNN - Case Study - Part 1.mp4 10.29Мб
Practical on CNN - Case Study - Part 2.mp4 28.31Мб
Practical on CNN - Case Study - Part 3.mp4 36.00Мб
Practical on CNN - Case Study - Part 4.mp4 13.22Мб
Practical on CNN - Case Study - Part 5.mp4 7.50Мб
Pseudocode.mp4 40.65Мб
Pseudocode.mp4 12.67Мб
Pseudocode for Batch.mp4 28.82Мб
Representations.mp4 158.08Мб
ResNet - Part 1.mp4 32.30Мб
ResNet - Part 2.mp4 28.15Мб
RNN Formula.mp4 29.21Мб
RNN - Part 1.mp4 9.87Мб
RNN Part 2.mp4 6.43Мб
SGD.mp4 38.95Мб
Sigmoid function.mp4 26.53Мб
Sigmoid Function.mp4 25.96Мб
Simplified Notations.mp4 29.40Мб
Stride and Padding.mp4 34.19Мб
Text Generation - Code generator case- study (Part-1).mp4 171.29Мб
Text Generation - Code generator case- study (Part-2).mp4 105.19Мб
Text Generation - Code generator case- study (Part-3).mp4 48.67Мб
Text Generation - Code generator case- study (Part-4).mp4 40.03Мб
Training for Batches.mp4 22.82Мб
Training in Neural Networks.mp4 32.74Мб
Training Neural Network - Part 1.mp4 122.56Мб
Training Neural Network - Part 2.mp4 56.79Мб
Training Neural Network - Part 3.mp4 110.75Мб
Training RNN.mp4 11.60Мб
Transfer Learning - Part 1.mp4 7.42Мб
Transfer Learning - Part 2.mp4 19.86Мб
Transfer Learning - Part 3.mp4 35.32Мб
Transfer Learning - Part 4.mp4 39.90Мб
Transfer Learning - Part 5.mp4 27.10Мб
Transfer Learning - Part 6.mp4 36.34Мб
Types of RNN - Part 1.mp4 7.41Мб
Types of RNN - Part 2.mp4 13.22Мб
Understanding Dimensions.mp4 58.63Мб
Understanding Human Brain.mp4 26.64Мб
Understanding MNIST.mp4 20.44Мб
Understanding Notations.mp4 99.95Мб
Vanishing Gradient.mp4 21.37Мб
Vectorised Methods.mp4 81.39Мб
VGG16 (Visual Geometry Group).mp4 44.63Мб
Video.mp4 40.00Мб
Weight and Bias.mp4 82.52Мб
Working with Flower Images - Case Study - Part 1.mp4 49.56Мб
Working with Flower Images - Case Study - Part 10.mp4 56.74Мб
Working with Flower Images - Case Study - Part 11.mp4 61.74Мб
Working with Flower Images - Case Study - Part 12.mp4 159.46Мб
Working with Flower Images - Case Study - Part 13.mp4 31.75Мб
Working with Flower Images - Case Study - Part 14.mp4 75.11Мб
Working with Flower Images - Case Study - Part 2.mp4 118.70Мб
Working with Flower Images - Case Study - Part 3.mp4 50.13Мб
Working with Flower Images - Case Study - Part 4.mp4 48.57Мб
Working with Flower Images - Case Study - Part 5.mp4 39.33Мб
Working with Flower Images - Case Study - Part 6.mp4 72.10Мб
Working with Flower Images - Case Study - Part 7.mp4 26.29Мб
Working with Flower Images - Case Study - Part 8.mp4 91.39Мб
Working with Flower Images - Case Study - Part 9.mp4 81.05Мб
Working with X-Ray images - Case Study - Part 1.mp4 9.03Мб
Working with X-Ray images - Case Study - Part 2.mp4 8.82Мб
Working with X-Ray images - Case Study - Part 3.mp4 14.09Мб
Working with X-Ray images - Case Study - Part 4.mp4 18.31Мб
Working with X-Ray images - Case Study - Part 5.mp4 26.57Мб
Working with X-Ray images - Case Study - Part 6.mp4 18.34Мб
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