Deep Learning with TensorFlow Training Course

Course CodeCourse Code

tf101

Duration Duration

21 hours (usually 3 days including breaks)

Requirements Requirements

  • Statistics
  • Python
  • (optional) A laptop with NVIDIA GPU that supports CUDA 8.0 and cuDNN 5.1, with 64-bit Linux installed

Overview Overview

TensorFlow is a 2nd Generation API of Google's open source software library for Deep Learning. The system is designed to facilitate research in machine learning, and to make it quick and easy to transition from research prototype to production system.

Audience

This course is intended for engineers seeking to use TensorFlow for their Deep Learning projects

After completing this course, delegates will:

  • understand TensorFlow’s structure and deployment mechanisms
  • be able to carry out installation / production environment / architecture tasks and configuration
  • be able to assess code quality, perform debugging, monitoring
  • be able to implement advanced production like training models, building graphs and logging

Course OutlineCourse Outline

Machine Learning and Recursive Neural Networks (RNN) basics

  • NN and RNN
  • Backprogation
  • Long short-term memory (LSTM)

TensorFlow Basics

  • Creation, Initializing, Saving, and Restoring TensorFlow variables
  • Feeding, Reading and Preloading TensorFlow Data
  • How to use TensorFlow infrastructure to train models at scale
  • Visualizing and Evaluating models with TensorBoard

TensorFlow Mechanics 101

  • Prepare the Data
    • Download
    • Inputs and Placeholders
  • Build the Graph
    • Inference
    • Loss
    • Training
  • Train the Model
    • The Graph
    • The Session
    • Train Loop
  • Evaluate the Model
    • Build the Eval Graph
    • Eval Output

Advanced Usage

  • Threading and Queues
  • Distributed TensorFlow
  • Writing Documentation and Sharing your Model
  • Customizing Data Readers
  • Using GPUs¹
  • Manipulating TensorFlow Model Files

TensorFlow Serving

  • Introduction
  • Basic Serving Tutorial
  • Advanced Serving Tutorial
  • Serving Inception Model Tutorial

¹ The Advanced Usage topic, “Using GPUs”, is not available as a part of a remote course. This module can be delivered during classroom-based courses, but only by prior agreement, and only if both the trainer and all participants have laptops with supported NVIDIA GPUs, with 64-bit Linux installed (not provided by NobleProg). NobleProg cannot guarantee the availability of trainers with the required hardware.

Bookings, Prices and EnquiriesBookings, Prices and Enquiries

Guaranteed to run even with a single delegate!
Private Classroom
 
Private Classroom
Participants are from one organisation only. No external participants are allowed. Usually customised to a specific group, course topics are agreed between the client and the trainer.
Private Remote
From £3300
Private Remote
The instructor and the participants are in two different physical locations and communicate via the Internet. More Information

The more delegates, the greater the savings per delegate. Table reflects price per delegate and is used for illustration purposes only, actual prices may differ.

Number of Delegates Private Remote
1 £3300
2 £2325
3 £2000
4 £1838
Public Classroom
From £3750
(97)
Public Classroom
Participants from multiple organisations. Topics usually cannot be customised

The more delegates, the greater the savings per delegate. Table reflects price per delegate and is used for illustration purposes only, actual prices may differ.

Number of Delegates Public Classroom
1 £3750
2 £2575
3 £2183
4 £1988
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Related Categories

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Upcoming Courses

VenueCourse DateCourse Price [Remote / Classroom]
EdinburghMon, 2018-02-05 09:30£3300 / £4800
Coventry - The QuadrantTue, 2018-02-06 09:30£3300 / £4050
Bradford - Carlisle Business CentreWed, 2018-02-07 09:30£3300 / £4050
Exeter - The SenateMon, 2018-02-12 09:30£3300 / £4200
NewcastleTue, 2018-02-13 09:30£3300 / £3900

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