Deep Learning for Computer Vision
The Complete Bootcamp

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What Our Bootcamp Covers

 

Image Recognition

Leverage deep learning and transfer learning to build powerful classification models

Object
Detection

Faster RCNN, SSD and YOLOv3

Learn how to train and evaluate these models

Image Segmentation

Learn how to use Mask RCNN to build powerful instance segmentation systems

Google AI Platform

Leverage cloud computing to train your models using powerful GPUs from Google

Tensorflow 2

Learn how use this deep learning framework to build computer vision systems

Docker

This tool will help as a machine learning engineer to make your code easily portable

Anaconda

Creating virtual environments is a must-have skill. Learn how to do that with Anaconda

Cloud Run

Deploying your deep learning models has never been easier using Google Cloud Run

What our students are saying

Why Choose AIFEE

3500+ students already enrolled

22+ hours of video content

You're stuck? We're always here to support you!

Computer Vision Freelancer

Hassan

Overall, the course was amazingly stunning. Appreciated the teaching style which included building from simplicity and encouragement to practice.

SDE Intern at Amazon

Vikram

This course is well designed and easy to learn. If you really want to have a good understanding of objects detection and its implementation, I recommend you this course. Thanks for providing such a wonderful course.

Deep Learning Enthusiast

Raju

Each course is categorized and explained in detail. Thanks for the course and support given during my learning.

Computer Vision Enthusiast

Roy

Truly awesome course. Each and every concept nicely and perfectly explained. Jr to Sr level people easily understand all the concepts and improve their skills. Highly recommend this course to learn and improve skill in Machine Learning!

Computer Vision Student

Amine

Thank you for the valuable course, I have benefited greatly from it.

Computer Vision Student

Mansouri

Thank you sir for your course. It was quite instructive, I liked the step by step process, by starting explaining what is image segmentation then you jumped to the code. Looking forward for the next course !

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What you will be getting

3 Courses & 3 AI projects
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Deep Learning for Image Recognition using Tensorflow 2 and Google Cloud Platform

  • Start from a real life dataset.

  • Train a deep learning model on your local machine.

  • Build a docker image to containerize your code.

  • Push the docker image to Google Container Registry.

  • Train you model using the docker image and Google AI Platform.

  • Deploy your trained model as a web app using Flask and Google Cloud Run.

  • Share the web app with recruiters to showcase your work.

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Deep Learning for Object Detection using Tensorflow 2 and Google Cloud Platform

  • Learn how object detection works using deep learning.

  • Learn how Faster RCNN, SSD and YOLOv3 work.

  • Start from a real life dataset of masked non-masked people.

  • Train 3 deep learning models : Faster RCNN, SSD and YOLOv3.

  • Train and evaluate your model on your local machine and on Google AI Platform.

  • Use your final models to make prediction on new images.

  • Put the project on your CV and share it with recruiters.

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Deep Learning for Image Segmentation using Tensorflow 2 and Google Cloud Platform

  • Learn how image segmentation works using deep learning.

  • Learn how Mask RCNN model works.

  • Start from a real life dataset of damaged cars.

  • Train Mask RCNN on your local machine and on Google AI Platform.

  • Use your final model to make predictions on new images.

  • Put the project on your CV and share it with recruiters.

Sneak peak into the projects you will be building
First AI project

You will train a deep learning model to recognize different types of food.

You will train it on your local machine and then on Google AI platform.

Finally, you will deploy your model as part of a web app using Flask and Google Cloud Run.

Second AI project

You will train and evaluate three of the most widely used deep learning models :

Faster-RCNN, SSD & YOLOv3.

These models will have an objective of detecting whether people are wearing masks or not.

You will do this on your local machine and also on Google AI Platform.

Third AI project

You will train a deep learning model to segment different parts of a car.

You will start from a raw dataset and how to annotate it.

Then you will train 

Mask RCNN model on your local machine and also on Google AI Platform.

Ready to build these projects yourself?

LIMITED TIME OFFER