Deep Learning with TensorFlow Training

Live Online & Classroom Enterprise Training

Master core concepts of Deep Learning with Google's TensorFlow - a distributed machine learning platform. Get industry ready to build deep learning models for different business domains in TensorFlow. Be the TensorFlow Expert your organization needs.

Looking for a private batch ?

REQUEST A CALLBACK
Key Features
  • Lifetime Access

  • CloudLabs

  • 24x7 Support

  • Real-time code analysis and feedback

  • 100% Money Back Guarantee

PDP BG 1
SpringPeople Logo

What is Deep Learning with TensorFlow training about?

Gain in-depth understanding of architecture of TensorFlow Core, API layers, and the use cases. Master all about unsupervised learning models, deep learning models and more. Start from installing and configuring TensorFlow, importing data, building a simple model to graduate to building complex layered models and architectures to crunch huge data sets leveraging the distributed, robust and scalable machine learning framework from Google. Implement Keras on top of TensorFlow to experiment with deep neural networks and tune machine learning models to produce more successful results.

In our cloud labs, through guided exercises practice building Handwritten digit recognition, regression models, deep learning and convolution models of computer vision.

Get ready to lead AI projects based on TensorFlow in your organization.

 

Suggested Audiences:

  • Data Scientists, Machine Learning Engineers, Researchers working on deep neural network models
  • Deep Learning / TensorFlow Enthusiasts

What are the objectives of Deep Learning with TensorFlow training?

The Deep Learning with TensorFlow Training enables you to:

  • Articulate the core arcitecture and API layers TensorFlow
  • Set up your computing environment and install TensorFlow
  • Build simple TensorFlow graphs for everyday computations
  • Apply logistic regression for classification with TensorFlow
  • Design and train a multilayer neural network with TensorFlow
  • Understand intuitively convolutional neural networks for image recognition
  • Bootstrap a neural network from simple to more accurate models
  • Lead ML/DL projects based on TensorFlow implementation

 

Available Training Modes

Live Online Training

Classroom Training

 

PDP BG 2

Who is Deep Learning with TensorFlow training for?

  • Anyone who wants to add Deep Learning with TensorFlow skills to their profile
  • Teams getting started on Deep Learning with TensorFlow projects
  • What are the prerequisites for Deep Learning with TensorFlow training?

    Mandatory:

    • Programming knowledge in Python
    • Fundamental level understanding of Machine Learning
    • Note: The above knowledge is must-have for the participants to fully appreciate the training content.
    • <... Read More

    Course Outline

    • Introduction and Installation of TensorFlow
      • What is a Tensor
      • What is TensorFlow
      • Installing Anaonda 5.0.1
      • Installing TensorFlow 1.4
      • Installing Keras
      • Getting Started with TensorFlow
      • Code basics
      • Graph visualization
      • Constants, Placeholders, Variables
      • Lab: Handwritten Digit Recognition Model using MNIST
    • Regression with TensorFlow
      • Linear Regression
      • Nonlinear Regression
      • Logistic Regression & Optimization using Loss Function
      • Activation Functions
      • Monitoring using TensorBoard
    • Unsupervised Learning Models
      • Use cases of Unsupervised Learning
      • K-means clustering
      • Restricted Boltzmann Machine
    • Deep Neural Networks (DNN)
      • Basic Neural Net
      • Single Hidden Layer Model
      • SHL Accuracy and Weights
      • Multiple Hidden Layer Models
      • Accuracy and Feature Extraction in MHL
      • Applying different optimization algorithms
      • Building Keras DNN
    • Convolutional Neural Networks
      • Theory and application of CNN
      • Pooling Layer Application
      • Font Classification using CNN
      • Hand-written digit recognition using CNN with Keras
    • Recurrent Neural Networks (RNN)
      • Theory and application of RNN
      • Long short-term memory
      • Recursive Neural Tensor Theory
      • Recurrent Neural Network Model

    Who is the instructor for this training?

    The trainer for this Deep Learning with TensorFlow has extensive experience in this domain, including years of experience training & mentoring professionals.

    Reviews