Email → Summary → Bookmark → Email
Free online RSS generator. Create RSS from any web page. Build RSS feed for your site or generate XML for personal usage
Say goodbye to slow, clunky containers and VMs. Run Docker and Linux on your Mac seamlessly and efficiently.
Exploratory Data Analysis (EDA) is the process of analyzing and summarizing the main characteristics of a data set, through visual and statistical methods. It’s an important step in the data science…
A package to manage complex workflows built on top off Laravel's queue.
A CLI Swiss Army Knife for ChatGPT. Contribute to npiv/chatblade development by creating an account on GitHub.
Click-through rate prediction is the task of predicting the likelihood that something on a website (such as an advertisement) will be clicked. <span style="color:grey; opacity: 0.6">( Image credit: [Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction](https://arxiv.org/pdf/1906.03776v2.pdf) )</span>
Click-through rate (CTR) estimation plays as a core function module in various personalized online services, including online advertising, recommender systems, and web search etc. From 2015, the success of deep learning started to benefit CTR estimation performance and now deep CTR models have been widely applied in many industrial platforms. In this survey, we provide a comprehensive review of deep learning models for CTR estimation tasks. First, we take a review of the transfer from shallow to deep CTR models and explain why going deep is a necessary trend of development. Second, we concentrate on explicit feature interaction learning modules of deep CTR models. Then, as an important perspective on large platforms with abundant user histories, deep behavior models are discussed. Moreover, the recently emerged automated methods for deep CTR architecture design are presented. Finally, we summarize the survey and discuss the future prospects of this field.
Consensus is a new search engine that uses AI to find you answers in scientific research. Find out what the research says in seconds with Consensus.
Using the One Time Operations package for Laravel, you can execute code one time after deployments just like you do it with migrations!
Convert code repos into an LLM prompt-friendly format. Mostly built by GPT-4. - GitHub - mpoon/gpt-repository-loader: Convert code repos into an LLM prompt-friendly format. Mostly built by GPT-4.