Deep Learning Training by Experts

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Our Training Process

Deep Learning - Syllabus, Fees & Duration

MODULE 1

  • Introduction to Tensor Flow
  • Computational Graph
  • Key highlights
  • Creating a Graph
  • Regression example
  • Gradient Descent
  • TensorBoard
  • Modularity
  • Sharing Variables
  • Keras Perceptrons
  • What is a Perceptron?
  • XOR Gate

MODULE 2

  • Activation Functions
  • Sigmoid
  • ReLU
  • Hyperbolic Fns, Softmax Artificial Neural Networks
  • Introduction
  • Perceptron Training Rule
  • Gradient Descent Rule

MODULE 3

  • 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

MODULE 4

  • Introduction to Convolutional Neural Networks
  • Introduction to CNNs
  • Kernel filter
  • Principles behind CNNs
  • Multiple Filters
  • CNN applications Introduction to Recurrent Neural Networks
  • Introduction to RNNs
  • Unfolded RNNs
  • Seq2Seq RNNs
  • LSTM
  • RNN applications

MODULE 5

  • Deep learning applications
  • Image Processing
  • Natural Language Processing
  • Speech Recognition
  • Video Analytics
  • Download Syllabus - Deep Learning
    This syllabus is not final and can be customized as per needs/updates
 
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Deep Learning Jobs in Mississauga

Enjoy the demand

Find jobs related to Deep Learning in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Mississauga, chennai and europe countries. You can find many jobs for freshers related to the job positions in Mississauga.

  • Software Engineer
  • Research Analyst
  • Data Analyst
  • Data Scientist
  • Data Engine
  • Image Recognition
  • Software Developer
  • Research Scientist
  • Instructor for Deep Learning
  • Applied Scientist

Deep Learning Internship/Course Details

Deep Learning internship jobs in Mississauga
Deep Learning This deep learning course in Mississauga is mainly recommended for software engineers, data scientists, data analysts, and statisticians who are interested in deep learning. Every day, businesses collect massive volumes of data and analyze it to get actionable business insights. Deep learning models in the real world could be used for driverless cars, money filtration, virtual assistants, facial recognition, and other applications. Rather than being numerical, the majority of the data is in an unstructured format, such as audio, image, text, and video. Because there is a strong demand for skilled deep learning engineers in various fields, this deep learning course in Mississauga certification training is ideal for intermediate and advanced experts. Deep learning is a subset of machine learning (ML), which is essentially a three-layer neural network. Participants in the deep learning course should have a thorough understanding of the principles of programming, as well as a solid understanding of the fundamentals of statistics and mathematics, as well as a clear grip on the critical knowledge portions of machine learning. Python is the language of deep learning. Deep learning has become increasingly significant for commercial decision-making since it is very adept at processing such forms of data. Deep learning teaches using botorganizeded anorganizedtured data.

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Internship/projects in mississauga
Internship/projects in mississauga
Internship/projects in mississauga
Internship/projects in mississauga
Internship/projects in mississauga
Internship/projects in mississauga
Internship/projects in mississauga

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