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UNIT 1
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Unit 1.1
1. 2 Building Intelligent Machines
1. 3 the Neurons
1.4 Training, Validation, and Test Sets
1.5 Gradient Descent with Sigmoidal Neurons
1.6 The Backpropagation Algorithm
1.7 Feed-Forward Neural Networks
1.8 Sigmoid, Tanh, and ReLU Neurons
puzzle
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Puzzle 1
puzzle 2
puzzle 3
Quiz
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Deep learning
CNN
Tensor Flow
Assignment
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Assignment 1
Assignment 2
Assignment 3
Assignment 4
Assignment 5
Tutorial link
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Link 1
00:00
Link 2
00:00
Link 3- Artificial Intelligence
00:00
Reference Link
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Link 1
00:00
Link 2
Link 3
Syllabus
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Syllabus
UNIT 2
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What Is TensorFlow
Installing TensorFlow
Creating and Manipulating TensorFlow Variables
TensorFlow Operations
The Challenges with Gradient Descent
Question Bank
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Question bank
unit 3
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Neurons in Human Vision
The Shortcomings of Feature Selection
Building a Convolutional Network for CIFAR-10
Full Architectural Description of Convolution Networks
Principal Component Analysis
Implementing an Autoencoder in TensorFlow
unit 4
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What is Artificial Intelligence?
Types of Machine Learning Algorithms
Introduction to Machine Learning
Knowledge Representation
unit 5
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What is Deep Learning?
Artificial Neural Network
The Convolutional Layer sub Field
Deeplearning and AI
Exercise Files
Building Intelligent Machines.pdf
Size: 292.58 KB
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