InceptionV3 - Inception Network
Detailed exploration of InceptionV3 architecture, covering its improvements over previous versions, including factorized convolutions, RMSProp optimizer, and label smoothing for enhanced CNN performance.
Explained Identity Block and Convolution Block in ResNet - Residual Networks
Practical explanation of identity and convolutional blocks in ResNet, including line-by-line code breakdown and discussion of residual concepts in deep learning architectures.
Convolutional Neural Networks
Explore convolutional neural networks for computer vision, covering feature extraction, convolution operations, and applications like object detection and self-driving cars.
How We Built a Job Recommender SaaS with Deep Learning to Disrupt the Job Market
Discover how deep learning and modern ML tools were used to create a multilingual job recommender system, revolutionizing job matching for a public employment service.
EfficientNet Paper Walkthrough
Comprehensive walkthrough of the EfficientNet paper, exploring model scaling, proposed methods, and results. Offers insights into innovative approaches for improving neural network efficiency.
Pretrained CNN Features for Semantic Segmentation Using Random Forest
Explore semantic segmentation using VGG16 features and Random Forest, offering improved results for limited training data compared to U-net.
SpineNet - Learning Scale-Permuted Backbone for Recognition and Localization
Explores SpineNet, a novel CNN architecture using scale-permuted features and cross-scale connections, outperforming traditional models in object detection and classification tasks.
A Friendly Introduction to Convolutional Neural Networks and Image Recognition
Friendly explanation of image recognition using Convolutional Neural Networks, covering basics to advanced concepts. Suitable for beginners, with minimal math required.
Convolutional Neural Networks
Explore convolutional neural networks for computer vision, covering feature extraction, convolution operations, and applications in autonomous navigation and medical imaging.
Convolutional Neural Networks
Explore convolutional neural networks for computer vision, covering feature extraction, convolution operations, and applications like object detection and self-driving cars.
Pytorch Image Captioning Tutorial
Learn to build an image captioning system from scratch using PyTorch, covering CNN and RNN implementation, training setup, and evaluation on the Flickr8k dataset.