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Computer Vision with TensorFlow

( Duration: 5 Days )

Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This Computer Vision with TensorFlow training course will explore TensorFlow 2, Google's open-source framework for machine learning. Join us to learn how to use convolutional neural networks (CNNs) for your visual tasks. This course starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network. You will discover the features that made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You will then move on to building, training, and deploying CNNs efficiently.

Complete with concrete code examples, this course shares how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In this course, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts.

By attending Computer Vision with TensorFlow workshop, delegates will learn to:

  • Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras
  • Apply modern solutions to a wide range of applications such as object detection and video analysis
  • Run your models on mobile devices and web pages and improve their performance.
  • Create your own neural networks from scratch
  • Classify images with modern architectures including Inception and ResNet
  • Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net
  • Tackle problems faced when developing self-driving cars and facial emotion recognition systems
  • Boost your application’s performance with transfer learning, GANs, and domain adaptation
  • Use recurrent neural networks (RNNs) for video analysis
  • Optimize and deploy your networks on mobile devices and in the browser

  • Basic Python skills
  • Good basic understanding of image representation (pixels, channels, etc.)
  • Understanding of Matrix manipulation (shapes, products, etc.)



Computer Vision and Neural Networks

  • Computer Vision and Neural Networks
  • Technical requirements
  • Computer vision in the wild
  • A brief history of computer vision
  • Getting started with neural networks

TensorFlow Basics and Training a Model

  • TensorFlow Basics and Training a Model
  • Technical requirements
  • Getting started with TensorFlow 2 and Keras
  • TensorFlow 2 and Keras in detail
  • The TensorFlow ecosystem

Modern Neural Networks

  • Modern Neural Networks
  • Technical requirements
  • Discovering convolutional neural networks
  • Refining the training process

Influential Classification Tools

  • Influential Classification Tools
  • Technical requirements
  • Understanding advanced CNN architectures
  • Leveraging transfer learning

Object Detection Models

  • Object Detection Models
  • Technical requirements
  • Introducing object detection
  • A fast object detection algorithm – YOLO
  • Faster R-CNN – a powerful object detection model

Enhancing and Segmenting Images

  • Enhancing and Segmenting Images
  • Technical requirements
  • Transforming images with encoders-decoders
  • Understanding semantic segmentation

Training on Complex and Scarce Datasets

  • Training on Complex and Scarce Datasets
  • Technical requirements
  • Efficient data serving
  • How to deal with data scarcity

Video and Recurrent Neural Networks

  • Video and Recurrent Neural Networks
  • Technical requirements
  • Introducing RNNs
  • Classifying videos

Optimizing Models and Deploying on Mobile Devices

  • Optimizing Models and Deploying on Mobile Devices
  • Technical requirements
  • Optimizing computational and disk footprints
  • On-device machine learning
  • Example app – recognizing facial expressions

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 6,000 various courses on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

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Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.