文化生活

投資理財

健康與情感

創作

Sela的創意花園的沙龍

关于财富和幸福的底层逻辑，一些思考和分享

拥有黄金和BTC是不会输的，除非你相信政治精英愿意忍受银行体系的彻底失败。

國際

職場產業

收好你的黄金和BTC，避开美国银行系统未来的灾难 | 硬核观点

就在这个劳动节假期，科技巨头IBM宣布：暂缓可以被AI取代的岗位的招聘，约7800人将被永久淘汰。这是6门可以帮助你领先于时代的免费课程。

學習

For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/3w46jar

This lecture covers:
1. The course (10min)
2. Human language and word meaning (15 min)
3. Word2vec algorithm introduction (15 min)
4. Word2vec objective function gradients (25 min)
5. Optimization basics (5min)
6. Looking at word vectors (10 min or less)

Key learning: The (really surprising!) result that word meaning can be representing rather well by a large vector of real numbers.

This course will teach:
1. The foundations of the effective modern methods for deep learning applied to NLP. Basics first, then key methods used in NLP: recurrent networks, attention, transformers, etc.
2. A big picture understanding of human languages and the difficulties in understanding and producing them
3. An understanding of an ability to build systems (in Pytorch) for some of the major problems in NLP. Word meaning, dependency parsing, machine translation, question answering.

To learn more about this course visit: https://online.stanford.edu/courses/cs224n-natural-language-processing-deep-learning  
To follow along with the course schedule and syllabus visit: http://web.stanford.edu/class/cs224n/ 

Professor Christopher Manning
Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science
Director, Stanford Artificial Intelligence Laboratory (SAIL)

0:00 Introduction
1:43 Goals
3:10 Human Language
10:07 Google Translate
10:43 GPT
14:13 Meaning
16:19 Wordnet
19:11 Word Relationships
20:27 Distributional Semantics
23:33 Word Embeddings
27:31 Word tovec
37:55 How to minimize loss
39:55 Interactive whiteboard
41:10 Gradient
48:50 Chain Rule

Stanford CS224N: NLP with Deep Learning | Winter 2021 | Lecture 1 - Intro & Word Vectors

IBM因AI淘汰了7800人，这是6门可以让你免于淘汰的免费AI课程

經過數月的探索和篩選，我精選了50個最適合個人作為參考的內容入口，分門別類，向各位免費分享這些資源。希望您也能從中找到適合您的Web3參謀信息。

Web3

一文通往50个Web3高價值内容庫，武裝您的第二大腦

中心化网络了帮助了全球数十亿人融入到互联网，并在其上创建了大量稳定、可靠的基础设施和应用。但与此同时，少数中心化巨头几乎垄断了互联网，甚至可以为所欲为。
Web3 是摆脱这一困境的方案。不同于科技巨头垄断的传统互联网，Web3 最重要的特征是去中心化，由所有用户构建、运营和拥有。

Web3 究竟是什么? 听听来自提出者的解释

web3 思想之根基：民有、民治、民享