Juan Carlos Olamendyjuancolamendy.hashnode.dev·Dec 7, 2023Unlocking the Power of Strided Convolutions in Neural NetworksHave you ever wondered how machines can recognize images or understand speech as efficiently as humans? The answer lies in a sophisticated aspect of neural networks known as strided convolutions. In this article, we will dive deep into the world of s...DiscussMachine Learning
Juan Carlos Olamendyjuancolamendy.hashnode.dev·Oct 19, 2023Back to Basics: Feature Extraction with CNNIf you've ever wondered how computers can see and understand the world through images, you're in for a treat! Today, we'll delve into the fascinating world of Convolutional Neural Networks (CNNs) and learn about their magical feature extraction powe...DiscussMachine Learning
Juan Carlos Olamendyjuancolamendy.hashnode.dev·Oct 19, 2023How Convnets works?Do you want to learn how Convnets works? Let's use MNIST, the hello world of #deeplearning Go through the steps of building and train a model. Load dataset First step is to load the MNIST dataset. It contains 70,000 28x28 images showing handwritten d...DiscussMachine Learning
Luvai Bhoriluvai.hashnode.dev·Aug 29, 2023Visual Intelligence Unleashed: The Magic of Deep Learning and CNNsIn an era where artificial intelligence is transcending boundaries and reshaping industries, there's a particular branch that stands out as a cornerstone of the AI revolution—deep learning. At the heart of this transformative force lies Convolutional...DiscussArtificial Intelligence
Testimony Adekoyawritingtestys.hashnode.dev·May 31, 2023Deep Dive into Convolutional Neural Networks, Part 1:Introduction Most models used in modern-day computer vision tasks like object detection, generative computer vision, object recognition, and so on all have their backbone architecture in convolutional neural networks (CNN). A convolutional neural net...Bhargav and 1 other are discussing this2 people are discussing thisDiscuss·4 likes·95 readsComputer Vision
Tinz TwinsProtinztwins.hashnode.dev·May 18, 2023Beginner's Guide to Convolutional Neural Networks using TensorFlow and KerasGenerated with Bing DALL-E Convolutional neural networks (CNNs) have been used in the industry for several years. The flexibility and handling of complex problems are what make CNNs so interesting. A convolutional neural network belongs to the deep l...DiscussArtificial Intelligence
Sudhanshu Wanitechblog01.hashnode.dev·Jan 24, 2023An Overview of Deep Learning for Image ClassificationImage classification is an area of computer vision focused on assigning labels to images based on their content. This is an important task for various applications such as B. Image search, object detection, and scene detection. Recent advances in d...Discuss·72 readsDeep Learning
Thomas Cherickalthomascherickal.hashnode.dev·Jan 1, 2023Part 3: Create Python Code to implement a deep learning convolutional neural network for MNISTSure! Here is some sample Python code that you can use to implement a deep learning convolutional neural network (CNN) for the MNIST dataset: import tensorflow as tf # Load the MNIST dataset (x_train, y_train), (x_test, y_test) = tf.keras.datasets.m...Discuss·2 likes·82 reads8 applications of all levels written in less than 10 minutes each using ChatGPTMNIS
Indirakumar SforQuasar Community Blogblog.quasarcommunity.org·Oct 13, 2022Convolutional neural networks(CNN)What is CNN? Convolutional neural networks (CNN/ConvNet) are a kind of deep neural network used most frequently to interpret visual data in deep learning. Normally, matrix multiplications come to mind when we think of a neural network, but that is no...Discuss·144 readspooling layer
Lawal Abdul-Azeez Ademolaabdul-azeez.hashnode.dev·Aug 22, 2022Handwritten Digit Text Recognition with Convolutional Neural NetworkIntroduction Convolutional Neural Network (CNN) is a deep learning technique used for image recognition and processing. Over the years, CNN has found a good grip over classifying images for computer visions and now it is being used in urban planning ...Discuss·72 readsMachine Learning
