Authorized Reprint Authors: Long Xinchen, Han Xiaoyang ◆ ◆ ◆ 1. Introduction You might not be familiar with this thing called ‘Machine Learning’, but when you lift your iPhone to take a photo, you are already accustomed to it helping you frame human faces; you naturally click on the news recommended by today’s headlines; you … Read more
In recent years, Uber’s self-driving cars, Google’s AlphaGo, quantitative trading, LinkedIn’s precise friend recommendations, and the Galapagos in Grasshopper that children are familiar with have all shown that machine learning is truly changing our lives, learning, and work. What Is Machine Learning? Machine learning is a data analysis method that can automatically generate analytical models. … Read more
Today, let’s talk about the things related to machine learning in Java, using the Weka library. Weka is a great tool that can handle data and run models, super convenient. Data Preprocessing, Let’s Go! In Weka, data processing is very smooth. Missing values? Noise? All sorted! It has a bunch of built-in filters, like weka.filters.unsupervised.attribute.Remove, … Read more
Machine Learning A magnificent history of artificial intelligence development The victory of AlphaGo, the success of autonomous driving, and breakthroughs in pattern recognition have repeatedly stimulated our nerves with the rapid development of artificial intelligence. As the core of artificial intelligence, machine learning has also attracted much attention in this rapid advancement, shining brightly. Today, … Read more
[Introduction] Embedding representation learning is a current research hotspot. From Word2Vec to Node2Vec to Graph2Vec, a large number of X2Vec algorithms have emerged. But how can we construct a theory of vector embeddings to guide algorithm design? Recently, Professor Martin Grohe, a computer science professor at RWTH Aachen University and ACM Fellow, gave a report … Read more
Summary of Word2vec Reference Materials Let me briefly describe my deep dive into Word2vec: I first looked at Mikolov’s two original papers on Word2vec, but found myself still confused after reading them. The main reason is that these papers omit too much theoretical background and derivation details. I then revisited Bengio’s 2003 JMLR paper and … Read more
Source | Wujie Community Mixlab Editor | An Ke 【PanChuang AI Introduction】: Recently, everyone has been flooded with the popular Qing Dynasty drama “Story of Yanxi Palace”~ The male lead, Emperor Qianlong, is often referred to as a “big pig’s hoof” by everyone because he falls in love with every woman he meets. As simple … Read more
I’ve been looking at word2vec for a long time, but I’ve found many different versions of explanations. Moreover, the original paper does not mention many details, so I plan to look at the source code directly. On one hand, it can deepen my understanding; on the other hand, I can make appropriate improvements in the … Read more
Author: Li Xuedong Editor: Li Xuedong Introduction: Nowadays, deep learning is all the rage. Deep learning has made significant progress in the field of image processing. With the release of Word2Vec by Google, deep learning has also sparked a frenzy in the field of Natural Language Processing (NLP). As I am currently working on … Read more
Word embeddings represent a word with a numerical vector, which is different from the IDs used in Tokenization. Word embedding vectors carry more semantic information. This article will illustrate Word2Vec: a method for word embeddings. This series also includes illustrations of Tokenization, Transformer, GPT2, and BERT. If you want to learn about Tokenization, please see … Read more