Best CNN Courses- https://mltut.com/best-convolutional-neural-network-resources/…

8 Best Convolutional Neural Network Resources

Source: https://www.mltut.com/best-convolutional-neural-network-resources/ Do you want to knowBest Convolutional Neural Network Resources?… If yes, this article is for you. In this article, you will find the8 Best Convolutional Neural Network Resources.

Now without any further ado, let’s get started-

1. What is Convolutional Neural Network?
2. 1. Intro to Deep Learning with PyTorch– Udacity
3. 2. Convolutional Neural Networks- deeplearning.ai
4. 3. Deep Learning– Udacity
5. 4. Deep Learning in Python– Datacamp
6. 5. Deep Learning: Convolutional Neural Networks in Python– Udemy
7. 6. Intro to TensorFlow for Deep Learning– Udacity
8. 7. Become a Computer Vision Expert– Udacity
9. 8. Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs– Udemy

Before I discuss the Best Convolutional Neural Network Resources, let’s see,What Convolutional Neural Network(CNN) is.

What is Convolutional Neural Network?

Convolutional Neural Network is an algorithm of Deep Learning. That is used for Image Recognition and Natural Language Processing. Convolutional Neural Network (CNN) takes an image to identify its features and predict it.

Yann Lecunis the father of the Convolutional Neural Network. He is a student of Geoffrey Hilton. Geoffrey Hilton is the father of Artificial Neural networks.

So let’s see how CNN works-

So, this is the basic structure of the Convolutional Neural Network. This input image may be anything, CNN takes this image to perform the operation and then classify it.

Convolutional Neural networks can be used inSentiment Analysis. That means it can detect that person ishappy or sadbased on the feature of the images.

This is an emoticon just for a reference, but CNN can identify the emotions of human faces. CNN gives theprobabilityfor example it can say 90% is the probability that the person is happy.

Now, let’s seeBest Convolutional Neural Network Resources–

1.****Intro to Deep Learning with PyTorch– Udacity****

**Time to Complete-**2 Months

This is aFREE deep learning online course.In this course, you will learn how to train aconvolutional networkto classifydog breeds from images of dogs. After that, you will learnstyle transferand how to buildrecurrent neural networks with PyTorch.

This course will also cover how to implement a network that learns fromTolstoy’s Anna Kareninato generate new text based on the novel. In the end, you will learnNatural Language Classificationand use your network to predict the sentiment of movie reviews.

Who Should Enroll?

• Those who are comfortable withPythonand data processing libraries such asNumPy and Matplotlib.

Interested to Enroll?

If yes, then start learning-Intro to Deep Learning with PyTorch

2.Convolutional Neural Networks– deeplearning.ai

**Time to Complete-**41 hours

**Rating-**4.9/5

In this course, you will understand the basics ofConvolutional Neural Networks.And learn the implementation of foundational layers of CNNs(pooling, convolutions).

After that, you will learn aboutTransfer Learningand how to apply transfer learning to your own deepConvolutional Neural Networks.

Object detectionis also covered in this course. In the end, you will explore the applications of CNN such asFace recognition & Neural Style Transfer.

Who Should Enroll?

• Those who have intermediate Python Skills.

Interested to Enroll?

If yes, then start learning-Convolutional Neural Networks

3.****Deep Learning– Udacity****

**Time to Complete-**4 months (If you spend 12 hours per week)

**Rating-**4.7/5

This Nanodegree program will teach you how to buildconvolutional networks for image recognition, recurrent networks for sequence generation, and****generative adversarial networks for image generation.

The instructorSebastian Thrunwill explain aboutdetecting skin cancer with CNN.This is anadvanced-level courseto understand the concepts of CNN and deep learning. This isnot for beginners.

Who Should Enroll?

• Those who haveintermediate-level Python programming knowledgeand experience withNumPy and pandas.
• And those who havemath knowledge, including- algebra and some calculus.

Interested to Enroll?

If yes, then start learning–Deep Learning (Udacity)

4.****Deep Learning in Python– Datacamp****

**Time to Complete-**20 hours

**Type-**Skill Track

This is a skill track offered byDatacamp.In this skill track, there are5 courses.

This skill track will teach you aboutconvolutional neural networksand how to use them to build much more powerful models which givemore accurate results.

Throughout this skill track, you will work on projects and learn how to accuratelypredict housing prices, credit card borrower defaults, and images of sign language gestures.This isnot for beginners.

Who Should Enroll?

• Those who have previous knowledge inMachine Learning and Python Programming.

Interested to Enroll?

If yes, then start learning–Deep Learning in Python

5.****Deep Learning: Convolutional Neural Networks in Python– Udemy****

**Rating-**4.7/5

**Time to Complete-**12 hours

This course is all aboutConvolutional Neural networks (CNN).

In this course, you will learn thefundamentals of CNNand how tobuild a CNN using Tensorflow 2.After that, you will learn how to doimage classification in Tensorflow 2and how to useEmbeddings in Tensorflow 2 for NLP.

If you are a beginner, then this course is not for you.

Who Should Enroll?

• Those who have an understanding of basic math (taking derivatives, matrix arithmetic, probability).

Interested to Enroll?

If yes, then check it outhere–Deep Learning: Convolutional Neural Networks in Python

6.****Intro to TensorFlow for Deep Learning– Udacity****

**Time to Complete-**2 months

This course will teach you aboutConvolutional Neural Networksand how to use a convolutional network to build more efficient models forFashion MNIST.

This is acompletely FREE course.During this course, you will work on a project where you will build aneural networkthat canrecognize images of articles of clothing.

Who Should Enroll?

• Those who know Python programming and basic algebra.

Interested to Enroll?

If yes, then start learning-Intro to TensorFlow for Deep Learning

7.Become a Computer Vision Expert–Udacity

**Rating-**4.7/5

**Provider-**Udacity

**Time to Complete-**3 months (If you spend 10-15 hours/week)

This Nanodegree program will teach youbasic image processingand building and customizingconvolutional neural networks.

Throughout the Nanodegree program, you will work on various projects such asfacial keypoint detection, automatic image captioning, and landmark detection & tracking.

This Nanodegree Program isnot for beginners.This is an advanced-level program where you will also learn techniquesused in self-driving car navigation and drone flight.

Who Should Enroll?

• Those who have intermediate-level knowledge inPython, statistics, machine learning, and deep learning.
• And those who have worked before with adeep learning frameworklikeTensorFlow, Keras, or PyTorch.

Interested to Enroll?

If yes, then check out all details here-Become a Computer Vision Expert

8.Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs****–Udemy

Rating– 4.5/5

**Provider-**SuperDataScience Team

**Time to Complete-**11 hours

In this course, you will learn what isFacial Recognition with OpenCV, object detection with SSD, and Image creation with GAN.

This course also covers the concepts ofartificial neural networks and convolutional neural networks.

Who Should Enroll?

• Those who havebasic python programmingknowledge andhigh-school-level math.

Interested to Enroll?

If yes, then check out all details here-Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs

And that’s all…So, these are the8Best Convolutional Neural Network Resources****. Now, it’s time to wrap up.

Conclusion

I hope these8Best Convolutional Neural Network Resources****will help you to learnCNNin detail. My aim is to provide you with the best resources for Learning. If you have any doubt or questions, feel free to ask me in the comment section.

Tell me in the comment section, which course you like.

All the Best!

Happy Learning!

Thank YOU!

Learn Deep Learning Basics****here.

Though of the Day…

**‘**Anyone who stops learning is old, whether at twenty or eighty. Anyone who keeps learning stays young. – Henry Ford

Written ByAqsa Zafar

Aqsa Zafar is a Ph.D. scholar in Machine Learning at Dayananda Sagar University, specializing in Natural Language Processing and Deep Learning. She has published research in AI applications for mental health and actively shares insights on data science, machine learning, and generative AI through MLTUT. With a strong background in computer science (B.Tech and M.Tech), Aqsa combines academic expertise with practical experience to help learners and professionals understand and apply AI in real-world scenarios.