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Deep learning for object detection using Tensorflow 2

Understand, train and evaluate Faster RCNN, SSD and YOLO v3 models using Tensorflow 2 and Google AI Platform
4.0
4.0/5
(126 reviews)
1,193 students
Created by

9.4

CourseMarks Score®

9.8

Freshness

8.4

Feedback

9.3

Content

Platform: Udemy
Video: 9h 51m
Language: English
Next start: On Demand

Top Object Detection courses:

Detailed Analysis

CourseMarks Score®

9.4 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

9.8 / 10
This course was last updated on 4/2021 .

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.4 / 10
We analyzed factors such as the rating (4.0/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.3 / 10
Video Score: 9.1 / 10
The course includes 9h 51m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 3 hours 13 minutes of 16 Object Detection courses on Udemy.
Detail Score: 9.4 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
8 resources.
0 exercise.
0 test.

Table of contents

Description

This course is designed to make you proficient in training and evaluating deep learning based object detection models. Specifically, you will learn about Faster R-CNN, SSD and YOLO models.
For each of these models, you will first learn about how they function from a high level perspective. This will help you build the intuition about how they work.
After this, you will learn how to leverage the power of Tensorflow 2 to train and evaluate these models on your local machine.
Finally, you will learn how to leverage the power of cloud computing to improve your training process. For this last part, you will learn how to use Google Cloud AI Platform in order to train and evaluate your models on powerful GPUs offered by google.
I designed this course to help you become proficient in training and evaluating object detection models. This is done by helping you in several different ways, including :
•Building the necessary intuition that will help you answer most questions about object detection using deep learning, which is a very common topic in interviews for positions in the fields of computer vision and deep learning.
•By teaching you how to create your own models using your own custom dataset. This will enable you to create some powerful AI solutions.
•By teaching you how to leverage the power of Google Cloud AI Platform in order to push your model’s performance by having access to powerful GPUs.

You will learn

✓ You will learn how Faster RCNN deep neural network works
✓ You will learn how SSD deep neural network works
✓ You will learn how YOLO deep neural network works
✓ You will learn how to use Tensorflow 2 object detection API
✓ You will learn how to train and evaluate deep neural networks for object detection such as Faster RCNN, SSD and YOLOv3 using your own custom data
✓ You will learn how to “freeze” your model to get a final model that is ready for production
✓ You will learn how to use your “frozen” model to make predictions on a set of new images using openCV and Tensorflow 2
✓ You will learn how to use Google Cloud AI platform in order to train your object detection models on powerful cloud GPUs
✓ You will learn how to use Tensorboard to visualize the development of the loss function and the mean average precision of your model
✓ You will learn how to change different parameters in order to improve your model’s performance

Requirements

• You need to have a basic level of Python (if you know what classes and functions are then you are good to go!)
• You need to have a basic understanding of what Tensorflow is.
• You don’t need any prior understanding of what object detection is, this is the mission of the course!

This course is for

• AI enthusiasts
• Data scientists
• Computer vision and machine learning students
• software developers
• Entrepreneurs

How much does the Deep learning for object detection using Tensorflow 2 course cost? Is it worth it?

The course costs $14.99. And currently there is a 25% discount on the original price of the course, which was $19.99. So you save $5 if you enroll the course now.
The average price is $23.9 of 16 Object Detection courses on Udemy.

Does the Deep learning for object detection using Tensorflow 2 course have a money back guarantee or refund policy?

YES, Deep learning for object detection using Tensorflow 2 has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Deep learning for object detection using Tensorflow 2 course, but there is a $5 discount from the original price ($19.99). So the current price is just $14.99.

Who is the instructor? Is Nour Islam Mokhtari a SCAM or a TRUSTED instructor?

Nour Islam Mokhtari has created 3 courses that got 214 reviews which are generally positive. Nour Islam Mokhtari has taught 3,521 students and received a 4.0 average review out of 214 reviews. Depending on the information available, Nour Islam Mokhtari is a TRUSTED instructor.
Computer Vision and Machine Learning engineer
My name is Nour-Islam Mokhtari and I am a machine learning engineer with a focus on computer vision applications. I have 3 years of experience developing and maintaining deep learning pipelines. I worked on several artificial intelligence projects, mostly focused on applying deep learning research to real world industry projects. My goal on Udemy is to help my students learn and acquire real world and industry focused experience. I aim to build courses that can make your learning experience smooth and  focused on the practical aspects of things!

9.4

CourseMarks Score®

9.8

Freshness

8.4

Feedback

9.3

Content

Platform: Udemy
Video: 9h 51m
Language: English
Next start: On Demand

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