Convolutional Neural Networks (CNNs) are one of the most important neural network algorithms in the present scenario. Tech giants like Google, Facebook, Amazon have been thoroughly using this neural network to perform and achieve a number of image-related tasks.
The applications of CNNs mostly includes the field of computer vision for image recognition, object detection, among others, This neural network is also being used for video inputs, speech recognition, sentence modelling, etc. in NLP models and more.
Below, we have curated a list of 10 best free online resources, in no particular order, to learn Convolutional Neural Networks (CNNs).
Convolutional Neural Networks
About: This course is a part of the Deep Learning Specialisation at Coursera. Here, you will learn how to build convolutional neural networks and apply them to image data. You will understand how to build a CNN model, understand the recent variations, know how to apply convolutional networks to visual detection as well as recognition tasks and more.
Know more here.
Introducing Convolutional Neural Networks
About: This tutorial is curated by the developers at Google. This tutorial, encompasses a brief introduction on convolution neural networks (CNNs), how it works, including hands-on training. You will learn topics like ReLU, pooling, fully connected layers and more.
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Convolution Neural Networks for Visual Recognition
About: This is a free course where you will learn about convolution neural networks and how they can be used in visual recognition. The tutorial starts with an architecture overview and then moves into ConvNet layers such as normalisation layer, fully connected layer, etc. including its architectures, such as layer patterns, computational considerations and more.
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Convolutional Neural Network Tutorial: From Basic to Advanced
About: In Convolutional Neural Network Tutorial: From Basic to Advanced, you will learn a basic description of the CNN architecture and its uses. The tutorial also provides two brief sessions to help you build and train a CNN using Keras and TensorFlow, respectively. You will learn about CNNs, applications of computer vision, CNNs in real-world and more.
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Convolutional Neural Network (CNN)
About: This is a tutorial on Convolutional Neural Network (CNN) provided by the TensorFlow developers. This tutorial demonstrates training a simple convolutional neural network to classify CIFAR images. You will learn how to import TensorFlow, prepare image dataset, verify data, create a convolutional base and other such.
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Convolutional Neural Network Tutorial – Developing An Image Classifier In Python Using TensorFlow
About: The tutorial, Convolutional Neural Network Tutorial – Developing An Image Classifier In Python Using TensorFlow is provided by Edureka. Here, you will understand what CNNs are, the architecture behind convolutional neural networks, layers such as ReLU, pooling, prediction of images using CNNs, among others.
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Convolutional Neural Networks in TensorFlow
About: This tutorial, Convolutional Neural Networks in TensorFlow, is a part of the DeepLearning.AI TensorFlow Developer Professional Certificate at Coursera. In this tutorial, you will learn advanced techniques to improve the computer vision model. Learners will be able to explore working with real-world images in different shapes and sizes, visualise the journey of an image through convolutions to figure out how a computer understands and grasps information, explore strategies and learn plot loss and accuracy to prevent overfitting, including augmentation and dropout.
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Convolutional Neural Networks tutorial – Learn how machines interpret images.
About: The tutorial, Convolutional Neural Networks tutorial – Learn how machines interpret images will help you understand how convolutional neural networks have become the backbone of the artificial intelligence industry and how CNNs are shaping industries of the future. The topics include what CNNs are, how it works, applications of CNNs, speech recognition using CNNs and much more.
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Convolutional Neural Networks with TensorFlow
About: In this tutorial, you’ll learn how to construct and implement Convolutional Neural Networks in Python with the TensorFlow framework. In this tutorial, learners will be introduced to tensors and how they differ from matrices, implementation of the convolutional neural network, how to construct the deep neural network model, among others.
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Convolutional Neural Networks (CNN)
About: This course is more like a hands-on practice than theory provided in Kaggle. Here you will learn how to load the dataset, introduction to CNNs, max pooling, same padding, implementing with Keras, evaluate CNN models, among others.
Know more here.
