Towards AI Editorial TeaminTowards AIHow did Binary Cross-Entropy Loss Come into Existence?Exploring the Genesis of Binary Cross-Entropy Loss FunctionMar 7, 20231Mar 7, 20231

Leo WanginTowards AIUNet++ Clearly Explained — A Better Image Segmentation ArchitectureIn this article, we are going to introduce you to UNet++, essentially an upgraded version of UNet. This article is designed to help you…Jul 22, 20221Jul 22, 20221

Neeraj KrishnainTowards Data ScienceUnderstanding and Implementing Faster R-CNN: A Step-By-Step GuideDemystifying Object DetectionNov 2, 202213Nov 2, 202213

Hrithick SeninAnalytics VidhyaUnderstanding GANs — Deriving the Adversarial loss from scratchGenerative adversarial networks or GANs for short are an unsupervised learning task where the generator model learns to discover patterns…Mar 3, 20212Mar 3, 20212

Lakshmi AjayinTowards Data ScienceDecoding the basic Math in GAN — Simplified VersionGANs have been a revolution in deep learning over the last decade. Since the first version of GAN that was released in 2014 by Ian…Feb 24, 2022Feb 24, 2022

Chiara CampagnolainTowards Data ScienceVisualizing regularization and the L1 and L2 normsWhy does minimizing the norms induce regularization?Oct 23, 2020Oct 23, 2020

Ekin TiuinTowards Data ScienceUnderstanding Latent Space in Machine LearningLearn a fundamental, yet often ‘hidden,’ concept of deep learningFeb 4, 202033Feb 4, 202033

Minh TraninTowards Data ScienceUnderstanding U-NetU-Net has become the go-to method for image segmentation. But how did it came to be?Nov 15, 20221Nov 15, 20221

Orhan G. YalçıninTowards Data ScienceImage Generation in 10 Minutes with Generative Adversarial NetworksUsing Unsupervised Deep Learning to Generate Handwritten Digits with Deep Convolutional GANs using TensorFlow and the MNIST DatasetSep 18, 20204Sep 18, 20204

KaushikladeImage Generation using Generative Adversarial Networks (GANs)Understanding the Generative Adversarial NetworkMar 24, 20211Mar 24, 20211

Richmond AlakeinTowards Data ScienceDeep Learning: Understand The Inception ModuleThe Deep Learning Architecture Inspired By An Internet Meme — and its technical information and detailsDec 22, 20203Dec 22, 20203

Siddhesh BangarResnet Architecture ExplainedIn their 2015 publication “Deep Residual Learning for Image Recognition,” Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun created a…Jul 5, 2022Jul 5, 2022

Vishal RajputinAIGuysYolov7: Making YOLO Great AgainYOLO V7 | yolov7 |🚀Object detection State-of-the-art in town🔥Jul 19, 20221Jul 19, 20221

Jamie DowatinAnalytics VidhyaInternal Covariate Shift: An Overview of How to Speed up Neural Network TrainingWhen beginning to build your first neural network, the process seems akin to feeling around for a needle in a haystack, blindfolded. There…Mar 29, 20212Mar 29, 20212

Alessandro PaticchioinTowards Data ScienceIntroduction to Reinforcement Learning: Temporal Difference, SARSA, Q-LearningReinforcement Learning is one of the most intricate fields of Machine Learning, due to its mathematical complexity, as well as the…Oct 11, 2022Oct 11, 2022

Eligijus BujokasinTowards Data ScienceEfficient memory management when training a deep learning model in PythonHow to use big data on a small computer using Tensorflow, Python and iteratorsOct 11, 2022Oct 11, 2022

Hari DevanathaninTowards Data ScienceThe Basics of Object Detection: YOLO, SSD, R-CNNOverview of how object detection works, and where to get startedOct 11, 20221Oct 11, 20221

Raz RotenberginTowards Data ScienceHow to Break GPU Memory Boundaries Even with Large Batch SizesOvercoming the problem of batch size and available GPU memory in training neural networksJan 19, 2020Jan 19, 2020

Daniel HuynhinTowards Data ScienceImplementing a batch size finder in Fastai : how to get a 4x speedup with better generalization !I will share with you my thoughts on batch size, show why a big one might help, and show how to find a good size using a paper from OpenAINov 4, 20191Nov 4, 20191

Renu KhandelwalinTowards Data ScienceConvolutional Neural Network: Feature Map and Filter VisualizationLearn how Convolutional Neural Networks understand images.May 18, 20206May 18, 20206