Deep Learning course (with TensorFlow)
Simplilearn Americas LLC
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 Description
Who are the trainers?
The Deep Learning training course sessions are delivered by highly qualified and certified instructors with relevant industry experience.Can I cancel my enrolment? Do I get a refund?
Yes, you can cancel your enrolment if necessary. We will refund the course price after deducting an administration fee. To learn more, you can view our Refund Policy.What payment options are available?
Payments can be made using any of the following options. You will be emailed a receipt after the payment is made.Visa Credit or Debit Card
MasterCard
American Express
Diner’s Club
PayPal
I’d like to learn more about this Deep Learning Training Course. Whom should I contact?
Contact us using the form on the right of any page on the Simplilearn website, or select the Live Chat link. Our customer service representatives will be able to give you more detailsWhat is Global Teaching Assistance?
Our teaching assistants are a dedicated team of subject matter experts here to help you get certified in your first attempt. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance.What is covered under the 24/7 Support promise?
We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum.
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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.
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