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Deep Learning course (with TensorFlow)

Course Summary

Simplilearn’s Deep Learning Course with TensorFlow will let you build, teach and implement Artificial Neural Networks using Deep Learning techniques. As part of the Deep Learning Tensorflow training, you will master the concepts of Deep Learning, TensorFlow, Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks to prepare you for the role of Deep Learning Scientist.


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    Course Syllabus


    Course preview

    Deep Learning with TensorFlow

    Introduction to TensorFlow

    Intro to TensorFlow

    Computational Graph

    Key highlights

    Creating a Graph

    Regression example

    Gradient Descent

    TensorBoard

    Modularity

    Sharing Variables

    Keras

    Perceptrons

    What is a Perceptron

    XOR Gate

    Activation Functions

    Sigmoid

    ReLU

    Hyperbolic Fns

    Softmax

    Artificial Neural Networks

    Introduction

    Perceptron Training Rule

    Gradient Descent Rule

    Gradient Descent and Backpropagation

    Gradient Descent

    Stochastic Gradient Descent

    Backpropagation

    Some problems in ANN

    Optimization and Regularization

    Overfitting and Capacity

    Cross Validation

    Feature Selection

    Regularization

    Hyperparameters

    Intro to Convolutional Neural Networks

    Intro to CNNs

    Kernel filter

    Principles behind CNNs

    Multiple Filters

    CNN applications

    Intro to Recurrent Neural Networks

    Intro to RNNs

    Unfolded RNNs

    Seq2Seq RNNs

    LSTM

    RNN applications

    Deep Learning applications

    Image Processing

    Natural Language Processing

    Speech Recognition

    Video Analytics

    That was just a sneak-peak into the lesson.
    Enroll for this course and get full access.
    Enroll now


Course Fee:
USD 599

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

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