Smarter Machine Learning for everyone using TensorFlow | Agilitics





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January 9, 2018
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Smarter Machine Learning for everyone using TensorFlow

$900.00 $780.00

TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well. This course teaches about Tensor flow and :

The topics include

  • Installing TensorFlow
  • Math Operations with TensorFlow
  • Neural Networks
  • Deep Learning
  • Image Processing with Convolutional Neural Network (CNN)
  • Language Processing with Recurrent Neural Network (RNN)
  • SKFlow

Course Plan

Lesson 1 Getting Started :2 hours

  • What is Deep Learning
  • What is Machine Learning
  • What is TensorFlow
  • Installing TensorFlow

Lesson 2 Simple Operations with TensorFlow :3 hours

  • Math Operations with TensorFlow
  • TensorFlow Data Structure
  • Complex Numbers
  • Fractals
  • Random Numbers

Lesson 3 Machine Learning with TensorFlow :2 hours

  • MNIST Dataset
  • Nearest Neighbour Classifier
  • Linear Regression Classifier
  • Logistic Regression Classifier
  • Clustering

Lesson 4 Neural Networks with TensorFlow 3 hours

  • Basic Netural Networks (NN)
  • Single Layer Perceptron
  • Multi Layer Perceptron
  • Deep Neural Networks

Lesson 5 Deep Learning 2 hours

  • Deep Learning Techniques
  • Convolutional Neural Networks (CNN)
  • Recurrent Neural Networks (RNN)

Lesson 6 Convolutional Neural Network Applications 2 hours

  • Image Processing with CNN

Lesson 7 Recurrent Neural Network Applications : 3 hours

  • Language Processing with RNN

Lesson 8 Sckit Learn and SKFlow :2 hours

  • Overview of Scikit Learn
  • Machine Learning with Scikit Learn
  • Neural Network with Scikit Learn
  • SkFlow
  • CNN on SKFlow
  • RNN on SKFlow

Lesson 9 What’s next :2 hours

  • The Future of TensorFlow
  • Alternatives of TensorFlow
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