table of Contents
4. Daniel (including blog and a public number, etc.)
1. Meeting
| name |
category |
|---|---|
| Conference on Machine Learning (ICML) |
International (the most important) |
| Conference on Neural Information Processing Systems (NIPS) |
International |
| Conference on Learning Theory (COLT) |
International |
| Field of artificial intelligence ( IJCAI ) |
International |
| Field of artificial intelligence ( AAAI) | International |
| Data mining (of KDD) |
International |
| Data mining (ICDM) |
International |
| Computer Vision and Pattern Recognition ( CVPR ) |
International |
| European Conference on Machine Learning (ECML) |
regional |
| Asian Conference on Machine Learning (ACML); |
regional |
| China Machine Learning Assembly (CCML) |
domestic |
| "Machine learning and its application" Seminar (MLA) |
domestic |
2. Journal
| name | category |
|---|---|
| Journal of Machine Learning Research |
International (the most important) |
| Machine Learning |
International (the most important) |
| Artificial Intelligence |
International (AI field) |
| Journal of Art cial Intelligence Rese rch |
International (AI field) |
| ACM Transactions on Knowledge Discovery from Data |
International (Data Mining) |
| Dαtα Mining and Knowledge Discovery |
International (Data Mining) |
| IEEE Transactions on Pattem Analysis and Machine Intelligence |
International (Computer Vision and Pattern) |
| Neural Computation |
International (neural networks) |
| IEEE Transa tions on Neural Networks αηd Le ming 8ystems |
International (neural networks) |
| "Electronic Journal", "Journal of Computers", "Journal of Software" | domestic |
| "Pattern Recognition and Artificial Intelligence" | domestic |
3. Books
| name | category |
|---|---|
| [Mitchell, 1997] |
getting Started |
| [Duda et al., 2001; Alcpaydin, 2004; Flach, 2012] |
入门 |
| [Witten et al， 2011] |
入门（基于 WEKA ） |
| 《机器学习》[周志华 20xx] | 入门（推荐） |
| 《统计学习方法》[李航， 2012] | 入门（推荐） |
| [Hastie et al., 2009] |
进阶 |
| [Bishop, 2006] |
进阶（贝叶斯爱好者） |
| [Shalev-Shwartz and Ben-David, 2014] |
进阶（理论型） |
| 《机器学习:一种人工智能途径》[Michalski et al., 1983] |
文献合集 |
| 《人工1.7 阅读材料 17 智能手册》系列 |
高阶 |
入门推荐的话当然是周志华老师的西瓜书《机器学习》了（默认已经有一定数学基础，概率论、线性代数等，不过此书对其要求不高），当然还有李航老师的《统计学习方法》
4.大牛（包括博客和公众号等）
| 名称 | 类别 |
|---|---|
| liuyubobobo（慕课网老师） | 讲得很通俗易懂，适合入门 |