Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
7 Hour(s) 20 Minute(s)
Language
English
Taught by
Ashar Siddiqui
Rating
2 views
Course Overview
Full Stack Computer Vision web app using python and Django, Transfer Learning, CNN, Keras, html, CSS, JavaScript, Ajax.
This Course has been designed for the developers who are able to train ML/DL models, but they struggle when it comes to saving the model for future use or when it comes to deploying the model through a full stack portal.
This course will teach you how to train and create computer vision model from scratch, how to utilize transfer learning for feature extraction, how to save those models using pickle, and how to deploy the models using Django framework.
Course Content
- 8 section(s)
- 43 lecture(s)
- Section 1 Course Overview
- Section 2 Project - Car Damage Detection (Computer Vision Model)
- Section 3 Django - Creating Full Stack Portal
- Section 4 Full Stack POC - Combining Client and Server Side
- Section 5 Deployment - Hosting your Django powered portal on world wide web
- Section 6 POC 2.0 - Code updates using AJAX
- Section 7 POC 3.0 - Integrating KYC web app to the portal
- Section 8 POC Upgrade to Django 3.2.2
What You’ll Learn
- Creating a full stack computer vision model using Transfer Learning in Python. The course will include details on how to create a computer vision model in python, and how to host it on server using Django.
- How to save and deploy any python ML/DL model you have created using Django.
- How to deploy a model in Production, Client Side(html, CSS) and Server side(Python) programming. All open source and free to use technologies.
- Learn Django and Integrating a python code with the Django Framework.
- How to create a user interface(UI) for your python code or ML/DL model that can take input from user, pass the input to your ML/DL model and renders back the results to UI.
- How to utilize transfer learning for feature extraction thus helping train new models without the need of a powerful GPU.
- Re-usability : how to quickly retrain the model that you create on new set of images.
- How to create an end to end computer vision project.
Reviews
-
GGITARTH RAJNEESH VAISHNAV
Could have been with a better GUI design
-
FFernão António Lopes Nobre Mouzinho
Yes. It was very good for me. Thank you
-
DDer Krikorian
Présentation du projet claire et détaillée. L'instructeur est très pédagogue.
-
GGaureesh Shenoy
Very well explained course and a very rare course which has end to end implementation for a Computer vision problem. Only issue is keras and tensorflow are bit complicated to use with gpu as the libraries get updated fast and give frequent errors - but then it cant be covered in any course.
