Deep Learning Online Live Class by Experts

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Deep Learning Online Live Classes in Bahla | Free Demo Training

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
 

    Course Highlights

  • Since 2001, Making IT Experts by Experts
  • Duration: 40 Hours (Vary as per your skill)
  • Course Fees
  • Individual Live Classes (1:1)
  • Batch Classes @ Low Fees
  • Training on Your Time, Any Where
  • Access to Recorded Videos
  • Practical Internship on Projects
  • 100% Placement Support by our jobsNEAR.in
  • Training/Internship Certificate
  • Our Locations

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Deep Learning Jobs in Bahla

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 Bahla, chennai and europe countries. You can find many jobs for freshers related to the job positions in Bahla.

  • 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 Bahla
Deep Learning Deep learning is a type of learning that entails Specialization in Bahla will assist you in learning the fundamental ideas of deep learning, as well as understanding the problems, repercussions, and capacities of deep learning, as well as allowing you to contribute to the advancement of cutting-edge technology. . Deep learning is a subset of machine learning (ML), which is essentially a three-layer neural network. Companies like to hire people who have completed this deep learning course. Deep learning teaches using botorganizeded anorganizedtured data. This deep learning course in Bahla is mainly recommended for software engineers, data scientists, data analysts, and statisticians who are interested in deep learning. Python is the language of deep learning. 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. Because there is a strong demand for skilled deep learning engineers in various fields, this deep learning course in Bahla certification training is ideal for intermediate and advanced experts. The foundations of deep learning and neural networks are covered, as well as techniques for improving neural networks, strategies for organizing and completing machine learning projects, convolutional neural networks, and their applications, recurrent neural networks and their methods and applications, and advanced topics such as deep reinforcement learning, generative adversarial networks, and adversarial attacks.

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