Artificial Intelligence using Tensarflow – TechSoft

Artificial Intelligence using Tensarflow

Artificial-Intelligence-using-Tensarflow

About This Course

AI and Deep Learning with Tensorflow program covers various Machine Learning Paradigms, how Deep Learning functions as a tools to achieve AI goals starting from Machine Learning. 

This course empowers you to master concepts of Neural Network Architecture, Regularisation for Deep Learning and Convolution Networks.

Learner will also develop the understanding of Computational Graphs unfolding, various types of neural networks in terms of Deep Learning, Boltzmann Machines and Deep Belief Networks.

Finally, learner will master the practical implementation of building and training neural networks, interpret and unfold patterns and correlations using Open Source Software Library – Tensorflow by Google.

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About This Course

AI and Deep Learning with Tensorflow program covers various Machine Learning Paradigms, how Deep Learning functions as a tools to achieve AI goals starting from Machine Learning. 

This course empowers you to master concepts of Neural Network Architecture, Regularisation for Deep Learning and Convolution Networks.

 

Learner will also develop the understanding of Computational Graphs unfolding, various types of neural networks in terms of Deep Learning, Boltzmann Machines and Deep Belief Networks.

Finally, learner will master the practical implementation of building and training neural networks, interpret and unfold patterns and correlations using Open Source Software Library – Tensorflow by Google.

Course Objectives

  • Understand various Machine Learning Paradigms
  • Understand Supervised & Unsupervised Learning Algorithms
  • Master basic concepts of Deep Learning
  • Learn practical aspects of Recurrent and Recursive Neural Networks
  • Understand large scale Deep Learning
  • Implement the learnt concept in a case study based Project

Curriculum

  • Module 1:Machine Learning Basics
  • Module 2:Introduction to Neural Nets and Deep Learning
  • Module 3:Introduction to TensorFlow
  • Module 4:Convolutional Networks
  • Module 5:Recurrent and Recursive Nets
  • Module 6:Unsupervised Learning: Autoencoders, RBM
  • Module 7:Practical Methodology
  • Module 8:Hands on Project

Course Pre-Requisite

Learner should have knowledge of a computer programming language preferably R or Python, Statistics & Probability and basic concepts of Machine Learning.

Course Calendar

Start Date End Date Duration Locaton Register Now
27th July 2019 28th July 2019 2 Days Pune Register Now
24th Aug 2019 25th Aug 2019 2 Days Pune Register Now
21th Sep 2019 22nd Sep 2019 2 Days Pune Register Now

Course Calendar

Stat Date

End Date Duration Location
27th July 2019 28th July 2019 2 Days Pune
Stat Date

End Date Duration Location
24th Aug 2019 25th Aug 2019 2 Days Pune
Stat Date

End Date Duration Location
21th Sep 2019 22th Sep 2019 2 Days Pune

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