Practical Deep Learning: Image Search Engine

Introduction 3 lectures 04:50 Where to get course materials Hi guys,The source code for the course and for the bonus part can be downloaded from my github profile. Please find it enclosed in the resource part for this lecture.Best Regards, Luka Example of Google Image Search and Styria.AI Dataset Introduction 3 lectures 04:50 Where to get course materials Hi guys,The source code for the course and for the bonus part can be downloaded from my github profile. Please find it enclosed in the resource part for this lecture.Best Regards, Luka Example of Google Image Search and Styria.AI Dataset Where to get course materials Hi guys,The source code for the course and for the bonus part can be downloaded from my github profile. Please find it enclosed in the resource part for this lecture.Best Regards, Luka Where to get course materials Hi guys,The source code for the course and for the bonus part can be downloaded from my github profile. Please find it enclosed in the resource part for this lecture.Best Regards, Luka Where to get course materials Hi guys,The source code for the course and for the bonus part can be downloaded from my github profile. Please find it enclosed in the resource part for this lecture.Best Regards, Luka Where to get course materials Hi guys,The source code for the course and for the bonus part can be downloaded from my github profile. Please find it enclosed in the resource part for this lecture.Best Regards, Luka Hi guys,The source code for the course and for the bonus part can be downloaded from my github profile. Please find it enclosed in the resource part for this lecture.Best Regards, Luka Hi guys,The source code for the course and for the bonus part can be downloaded from my github profile. Please find it enclosed in the resource part for this lecture.Best Regards, Luka Example of Google Image Search and Styria.AI Example of Google Image Search and Styria.AI Example of Google Image Search and Styria.AI Example of Google Image Search and Styria.AI Dataset Dataset Dataset Dataset Dataset preprocessing and helper functions 6 lectures 18:51 Import project dependencies Image loader function Dataset preprocesing function Cosine distance Hamming distance Sparse accuracy function Dataset preprocessing and helper functions 6 lectures 18:51 Import project dependencies Image loader function Dataset preprocesing function Cosine distance Hamming distance Sparse accuracy function Import project dependencies Import project dependencies Import project dependencies Import project dependencies Image loader function Image loader function Image loader function Image loader function Dataset preprocesing function Dataset preprocesing function Dataset preprocesing function Dataset preprocesing function Cosine distance Cosine distance Cosine distance Cosine distance Hamming distance Hamming distance Hamming distance Hamming distance Sparse accuracy function Sparse accuracy function Sparse accuracy function Sparse accuracy function Model Util functions 5 lectures 18:02 Model inputs Convolutional block function Dense block function Optimization and loss functions Building the model Model Util functions 5 lectures 18:02 Model inputs Convolutional block function Dense block function Optimization and loss functions Building the model Model inputs Model inputs Model inputs Model inputs Convolutional block function Convolutional block function Convolutional block function Convolutional block function Dense block function Dense block function Dense block function Dense block function Optimization and loss functions Optimization and loss functions Optimization and loss functions Optimization and loss functions Building the model Building the model Building the model Building the model Training and testing 5 lectures 27:12 Training function - part 1 Training function - part 2 Training the model Creating training set vectors First phase testing Training and testing 5 lectures 27:12 Training function - part 1 Training function - part 2 Training the model Creating training set vectors First phase testing Training function - part 1 Training function - part 1 Training function - part 1 Training function - part 1 Training function - part 2 Training function - part 2 Training function - part 2 Training function - part 2 Training the model Training the model Training the model Training the model Creating training set vectors Creating training set vectors Creating training set vectors Creating training set vectors First phase testing First phase testing First phase testing First phase testing Putting the model in production 6 lectures 24:25 File organization Flask app - part 1 Flask app - part 2 HTML templates Full application testing What's next? The pipeline that we currently have is pretty good, but we can improve it even further! Let’s go through potential steps that you can take to improve the pipeline that we have created in the course and create a great image-search product.

Use color features as an additional search filter

TensorFlow Serving pipeline version

Use Hourglass attention mechanism to enhance models performance

Use a model pre-trained on ImageNet

These are some of the go-to ideas on how you can improve the pipeline even further. For bonus content I’ll get you going by explaining the first two improvements. Putting the model in production. 6 lectures 24:25 File organization Flask app - part 1 Flask app - part 2 HTML templates Full application testing What's next? The pipeline that we currently have is pretty good, but we can improve it even further! Let’s go through potential steps that you can take to improve the pipeline that we have created in the course and create a great image-search product