A complete guide on how to build Image Search Engine

Description

Course Description

Learn to build image SEARCH  engine with using deep learning .  Deep learning is popular where a machine can be trained to search images based on patterns in the images.  Once trained, it can be used to search for similar images.

A lot of smart researchers have already spent lot of time building really good image classification networks like VGGNET, RESNET, Inception V3. The networks are variants of CNN. These networks have been trained on imagenet animal dataset. If your dataset requires a different type of image classification, you could just start with these networks and fine tune them on your smaller dataset. This saves significant time and resources. We are going to leverage VGG in this course.

Build a strong foundation in image search engines  with this tutorial for beginners.

• Understanding fundamentals image search

• Understanding fundamentals of deep learning , CNN and VGG

• Benefits of VGG and Glove embeddings

• Learn to use image and text embeddings

• Understand approximate nearest neighbor algorithm

• Use Spotify's Annoy index  for faster retrieval

• Learn how to apply VGG with real example of visual similarity search

• Use Jupyter Notebook for step by step programming

• Fine tune accuracy of model for performing text to image and image to text search

• Build a real life web application for visual similarity search classification

  
  

• A Powerful Skill at Your Fingertips  Learning the fundamentals image search  puts a powerful and very useful tool at your fingertips. Python and Jupyter are free, easy to learn, has excellent documentation.

No prior knowledge of CNN or deep learning is assumed. I'll be covering topics like deep learning, Convolution and CNN   from scratch.

Jobs in image search area are plentiful, and being able to learn transfer learning will give you a strong edge. Image embedding is  state of art technology that can quickly help you achieve your goal.

Learning image search with VGG will help you become a computer vision developer which is in high demand.

Content and Overview  

This course teaches you on how to build image search engine using open source Python and Jupyter framework.  You will work along with me step by step to build following answers

• Introduction to image search engine

• Introduction to image embeddings and text embeddings

• Build an jupyter notebook step by step using VGG

• Build a real world web application to find cat vs dog

What am I going to get from this course?

• Learn VGG and build image search classification engine from professional trainer from your own desk.

• Over 10 lectures teaching you how to build image search engine

• Suitable for beginner programmers and ideal for users who learn faster when shown.

• Visual training method, offering users increased retention and accelerated learning.

• Breaks even the most complex applications down into simplistic steps.

• Offers challenges to students to enable reinforcement of concepts. Also solutions are described to validate the challenges.

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