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Convolutional Neural Networks for Medicine

AI uses for Medical Imagery
5.0
5.0/5
(3 reviews)
7 students
Created by

9.8

CourseMarks Score®

10.0

Freshness

10.0

Feedback

8.8

Content

Platform: Udemy
Video: 30m
Language: English
Next start: On Demand

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Detailed Analysis

CourseMarks Score®

9.8 / 10

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

Freshness Score

10.0 / 10
This course was last updated on 1/2022.

Course content can become outdated quite quickly.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

10.0 / 10
We analyzed factors such as the rating (5.0/5) 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

8.8 / 10
Video Score: 7.6 / 10
The course includes 30m 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.
Detail Score: 9.3 / 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.
1 resources.
0 exercise.
0 test.

Table of contents

Description

Before starting this course you must at least have an intermediate level of python, basic understanding of convolutional neural networks, and basic knowledge of Tensorflow. By the end of this course you will learn how to train very accurate convolutional neural networks to predict test images for binary class. You know enough to where if you want to go off on your own and use your own methods how to do that. Also appropriate parameters to use as well as data augmentation methods. It is explained in this course how to train multiclass as well.  Not to mention you will learn how to use CV2 when predicting an image after training the convolutional neural network. You will also learn how to train a multi class Convolutional Neural Network and predict as well. Then learn to use a Keras Load Model Function for both binary and multi class predictions. Although the videos are short they are thoroughly and simply explained. You will also learn to deal with some of the challenges in deep learning as well when it comes to small dataset size. All the datasets featured in this video are found on Kaggle, except one that I provide to you directly. I will explain why in that video. Do not worry about the quizzes if you pay attention you will easily do great. But most importantly be ready to learn. This is not is challenging as it seems. I show you how to prevent overfitting and reduce bias severely with these methods in these videos.

You will learn

✓ Convolutional Neural Networks
✓ Data Augmentation
✓ Tensorflow
✓ Binary Class Predictions with percentages of each class
✓ Keras
✓ Maxpooling
✓ CV2
✓ AI uses for Medical Imagery
✓ Creating a Train and Validation Set when the original dataset only has one folder
✓ Dealing with Overfitting
✓ Dealing with a very Small Dataset

Requirements

• Intermediate Python Knowledge
• Basic Tensorflow Knowledge
• Either have an Google Colab. Or if using Jupyter Notebook Tensorflow and Keras already installed in the virtual environment
• Have a basic idea of convolutional neural networks

This course is for

• Those trying to improve their skills convolutional neural networks
• Those who want to find medical uses for convolutional neural networks
• Those who want to learn how to get an Image Classification model to predict test pictures
• Those that want to learn ways to improve accuracy when building Image Classification models

How much does the Convolutional Neural Networks for Medicine course cost? Is it worth it?

The course costs $12.99. And currently there is a 80% discount on the original price of the course, which was $64.99. So you save $52 if you enroll the course now.

Does the Convolutional Neural Networks for Medicine course have a money back guarantee or refund policy?

YES, Convolutional Neural Networks for Medicine 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 Convolutional Neural Networks for Medicine course, but there is a $52 discount from the original price ($64.99). So the current price is just $12.99.

Who is the instructor? Is Marshall Trumbull a SCAM or a TRUSTED instructor?

Marshall Trumbull has created 4 courses that got 13 reviews which are generally positive. Marshall Trumbull has taught 18 students and received a 4.8 average review out of 13 reviews. Depending on the information available, Marshall Trumbull is a TRUSTED instructor.
Machine Learning Engineer
I have 43 various certifications in Machine Learning, Deep Learning, and Reinforcement Learning as well as deployments on Various Clouds. Including AI for Medicine. Also in Python for Cybersecurity, Django, and Big Data. I have alot of experience on AWS using Sagemaker. As well of GCP and IBM cloud as well. Outside of machine learning in IT some backend web development with Django. But machine learning is my specialty. I have worked as a freelancer for a while now.

9.8

CourseMarks Score®

10.0

Freshness

10.0

Feedback

8.8

Content

Platform: Udemy
Video: 30m
Language: English
Next start: On Demand

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