Tensorflow Deep Learning Solutions for Images [Video]

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Tensorflow Deep Learning Solutions for Images [Video]

Will Ballard

Use Tensorflow's capabilities to perform efficient deep learning on Images
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Video Details

ISBN 139781788396899
Course Length1 hour and 25 minutes

Video Description

Tensorflow is Google’s popular offering for machine learning and deep learning. It has quickly become a popular choice of tool for performing fast, efficient, and accurate deep learning. This course presents the implementation of practical, real-world projects, teaching you how to leverage Tensforflow’s capabilties to perform efficient deep learning.

In this video, you will be acquainted with the different paradigms of performing deep learning such as deep neural nets, convolutional neural networks, recurrent neural networks, and more, and how they can be implemented using Tensorflow.

This will be demonstrated with the help of end-to-end implementations of three real-world projects on popular topic areas such as natural language processing, image classification, fraud detection, and more. By the end of this course, you will have mastered all the concepts of deep learning and their implementation with Tensorflow and Keras.

Style and Approach

This course takes a step-by-step approach, helping you explore all the functioning of TensorFlow.

Table of Contents

Machine Learning Toolkit
The Course Overview
Installing Docker
The Machine Learning Dockerfile
Sharing Data
Machine Learning REST Service
Image Data
MNIST Digits
Tensors: Just Multidimensional Arrays
Turning Images into Tensors
Turning Categories into Tensors
Classical Neural Network
Classical/Dense Neural Network
Activation and Non Linearity
Softmax
Training and Testing Data
Dropout and Flatten
Solvers
Hyperparameters
Grid Search
Convolutional Neural Network
Convolutions
Pooling
Convolutional Neural Network
Deep Neural Network
An Image Classification Server
REST API Definition
Trained Models in Docker Containers
Making Predictions

What You Will Learn

  • Set up a Machine Learning environment
  • Work with Docker and Keras
  • Process images for machine vision
  • Process text for Natural language understanding
  • Work with tabular data to make financial predictions
  • Generate synthetic test data with machine learning

Authors

Table of Contents

Machine Learning Toolkit
The Course Overview
Installing Docker
The Machine Learning Dockerfile
Sharing Data
Machine Learning REST Service
Image Data
MNIST Digits
Tensors: Just Multidimensional Arrays
Turning Images into Tensors
Turning Categories into Tensors
Classical Neural Network
Classical/Dense Neural Network
Activation and Non Linearity
Softmax
Training and Testing Data
Dropout and Flatten
Solvers
Hyperparameters
Grid Search
Convolutional Neural Network
Convolutions
Pooling
Convolutional Neural Network
Deep Neural Network
An Image Classification Server
REST API Definition
Trained Models in Docker Containers
Making Predictions

Video Details

ISBN 139781788396899
Course Length1 hour and 25 minutes
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