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    UNIT 1
    0/8
    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
    0/3
    Puzzle 1
    puzzle 2
    puzzle 3
    Quiz
    0/3
    Deep learning
    CNN
    Tensor Flow
    Assignment
    0/5
    Assignment 1
    Assignment 2
    Assignment 3
    Assignment 4
    Assignment 5
    Tutorial link
    0/3
    Link 1
    00:00
    Link 2
    00:00
    Link 3- Artificial Intelligence
    00:00
    Reference Link
    0/3
    Link 1
    00:00
    Link 2
    Link 3
    Syllabus
    0/1
    Syllabus
    UNIT 2
    0/5
    What Is TensorFlow
    Installing TensorFlow
    Creating and Manipulating TensorFlow Variables
    TensorFlow Operations
    The Challenges with Gradient Descent
    Question Bank
    0/1
    Question bank
    unit 3
    0/6
    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
    0/4
    What is Artificial Intelligence?
    Types of Machine Learning Algorithms
    Introduction to Machine Learning
    Knowledge Representation
    unit 5
    0/3
    What is Deep Learning?
    Artificial Neural Network
    The Convolutional Layer sub Field
    Deeplearning and AI

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