Selected from echen Translated by Machine Heart Contributors: Machine Heart Editorial Team Long Short-Term Memory (LSTM) is a crucial neural network technology that has been widely applied in many fields, including speech recognition and natural language processing. In this article, Edwin Chen provides a systematic introduction to LSTM. Machine Heart has translated this article. The … Read more
Previously, I introduced Recurrent Neural Networks (RNNs), which are fascinating because they can effectively utilize historical information. For instance, using the previous video frame to infer the current video content. In earlier articles, we also discussed that traditional RNNs cannot learn connections that are too far apart in time. Sometimes, we only need the previous … Read more
Compiled and Organized by Annie Ruo Po | QbitAI WeChat Official Account Author Bio: Edwin Chen, researching mathematics/linguistics at MIT, speech recognition at Microsoft Research, quantitative trading at Clarium, advertising at Twitter, and machine learning at Google. In this article, the author first introduces the basic concepts of neural networks, RNNs, and LSTMs, then compares … Read more
(Click the public account above to follow quickly) Source: CodeMeals cnblogs.com/fengfenggirl/p/bp_network.html If you have good articles to submit, please click → here for details Neural networks were once very popular, went through a period of decline, and are now gaining popularity again due to deep learning. There are many types of neural networks: feedforward networks, … Read more
This article will coverthe essence of the Loss Function principles of the Loss Functionand the algorithms to help you understand the Loss Function Loss Function . Loss Function 1.Loss Function essence Machine Learning’s “Three Steps”:Select a family of models,define the loss function to quantify prediction errors,and find the optimal model parameters that minimize the loss … Read more
▌1. Introduction: As a beginner in AI, I referenced some articles and wanted to take some notes to deepen my understanding. I am sharing this for those who need it, and I hope it helps others as well! [Toxic Chicken Soup]: Algorithms often leave you in a state of confusion –> “Who am I, where … Read more
Hello everyone, I am Xiao Wu Ge. It has been a while since my last update. Recently, I have been looking at various topics, and I don’t know where to start. I have been quite busy with work, but I managed to find some time this weekend to write an article. Most of the articles … Read more
Developing artificial intelligence systems with advanced reasoning capabilities is a long-standing research problem. Traditionally, the main strategy for addressing this challenge involves the use of symbolic methods, where knowledge is explicitly represented through symbols and implemented through explicitly programmed rules. However, with the emergence of machine learning, systems have shifted towards being able to learn … Read more
Editorial Team WeChat Official Account KeywordsFull Network SearchLatest Ranking “Quantitative Investment”: Ranked First “Quant”: Ranked First “Machine Learning”: Ranked Fourth We will continue to work hard To become ahigh-qualityfinancial and technical public account Translation by: mchoi [Series 1]Neural Networks for Algorithm Trading Based on Multivariate Time Series(Click the title to read) In this article, we … Read more
This article will explain the essence of Back Propagation, its principles, and provide examples to help you understand Back Propagation in one read. Back Propagation 1. The Essence of Back Propagation Forward Propagation: Forward propagation is the process by which a neural network transforms input data into prediction results through its hierarchical structure and parameters, … Read more