Convolutional Neural Networks | CNN With TensorFlow | CNN Tutorial for Beginners | CNN | Simplilearn

🔥IITK – Advanced Executive Program in Cybersecurity – https://www.simplilearn.com/ai-cybersecurity-course?utm_campaign=Dec24Exp&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥IITM – AI-Powered Cybersecurity Mastery – https://www.simplilearn.com/ai-cybersecurity-course?utm_campaign=ONBmh61NoHw&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Cyber Security Expert Masters Program – https://www.simplilearn.com/cyber-security-expert-master-program-training-course?utm_campaign=ONBmh61NoHw&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥IIITB – Advanced Executive Program in Cybersecurity (India Only) – https://www.simplilearn.com/pgp-advanced-executive-program-in-cyber-security?utm_campaign=ONBmh61NoHw&utm_medium=DescriptionFirstFold&utm_source=Youtube

The convolutional Neural Networks tutorial by Simplilearn will take you through the concept of CNN With TensorFlow and why we use it. This CNN tutorial with Python explains Conventional Neural Networks with a suitable example. In addition, we will use the MNIST dataset to demonstrate the concept of Conventional Neural Networks in image classification. Below are the topics we are covering in this CNN tutorial for beginners.

00:00 Convolutional Neural Networks tutorial for beginners
01:38 What is Convolutional Neural Networks ?
03:18 How does CNN recognize images?
04:06 Layers in CNN
04:25 Convolution Layer
04:53 ReLU Layer
05:37 Pooling Layer
06:21 Structure of CNN
07:12 How exactly does CNN recognize an image
08:05 Hands-on lab Demo

Layers in a Convolutional Neural Network
Convolution layer:- This is the first step in the process of extracting valuable features from an image. A convolution layer has several filters that perform the convolution operation. Every image is considered a matrix of pixel values.

ReLU layer:- ReLU stands for the rectified linear unit. Once the feature maps are extracted, the next step is to move them to a ReLU layer.
ReLU performs an element-wise operation and sets all the negative pixels to 0. It introduces non-linearity to the network, and the generated output is a rectified feature map.

Pooling layer:- Pooling is a down-sampling operation that reduces the dimensionality of the feature map. The rectified feature map now goes through a pooling layer to generate a pooled feature map.

✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

✅ Watch More Videos On Deep Learning By Simplilearn: https://youtube.com/playlist?list=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip

#CNN #ConventionalNeuralNetworks #CNNwithTensorFlow #CNNTutorialForBeginners #DeepLearning #DeepLearningTutorial #Datasciencecourse #DataScience #SimplilearnMachineLearning #DeepLearningCourse #Simplilearn

➡️ Professional Certificate Program In AI And Machine Learning

✅ Key Features
– Professional Certificate Program certificate and Alumni Association membership
– Exclusive hackathons and Ask me Anything sessions by IBM
– 8X higher live interaction in live online classes by industry experts
– 3 Capstones and 25+ Projects with industry data sets from Twitter, Uber, Mercedes Benz, and many more
–
– Simplilearn’s JobAssist help

✅ Skills Covered
– Statistics
– Python
– Supervised Learning
– Unsupervised Learning
– NLP
– Neural Networks
– Computer Vision
-GANs
– Keras
– Tensorflow
– Reinforcement Learning
– Speech Recognition
– Recommendation Systems
– Ensemble Learning
– NumPy

👉Learn More at: https://www.simplilearn.com/professional-aiml-program?utm_campaign=10March2023CNNTutorialforBeginners&utm_medium=Description&utm_source=youtube