学习NLP,AI,Deep Learning 的牛逼的教程_coursera piazza

1.Andrew Moore。卡内基梅隆计算机学院的院长大大。这些基本上涵盖了很多的数据挖掘topic。

• Decision Trees
• Information Gain
• Probability for Data Miners
• Probability Density Functions
• Gaussians
• Maximum Likelihood Estimation
• Gaussian Bayes Classifiers
• Cross-Validation
• Neural Networks
• Instance-based learning (aka Case-based or Memory-based or non-parametric)
• Eight Regression Algorithms
• Predicting Real-valued Outputs: An introduction to regression
• Bayesian Networks
• Inference in Bayesian Networks (by Scott Davies and Andrew Moore)
• Learning Bayesian Networks
• A Short Intro to Naive Bayesian Classifiers
• Short Overview of Bayes Nets
• Gaussian Mixture Models
• K-means and Hierarchical Clustering
• Hidden Markov Models
• VC dimension
• Support Vector Machines
• PAC Learning
• Markov Decision Processes
• Reinforcement Learning
• Biosurveillance: An example
• Elementary probability and Naive Bayes classifiers
• Spatial Surveillance
• Time Series Methods
• Game Tree Search Algorithms, including Alpha-Beta Search
• Zero-Sum Game Theory
• Non-zero-sum Game Theory
• Introductory overview of time-series-based anomaly detection algorithms
• AI Class introduction
• Search Algorithms
• A-star Heuristic Search
• Constraint Satisfaction Algorithms, with applications in Computer Vision and Scheduling
• Robot Motion Planning
• HillClimbing, Simulated Annealing and Genetic Algorithms

2. 

斯坦福大学在三月份开设了一门“深度学习与自然语言处理”的课程：CS224d: Deep Learning for Natural Language Processing，授课老师是青年才俊 Richard Socher，他本人是德国人，大学期间涉足自然语言处理，在德国读研时又专攻计算机视觉，之后在斯坦福大学攻读博士学位，拜师NLP领域的巨牛 Chris Manning 和 Deep Learning 领域的巨牛Andrew Ng，其博士论文是《Recursive Deep Learning for Natural Language Processing and Computer Vision》，也算是多年求学生涯的完美一击。毕业后以联合创始人及CTO的身份创办了MetaMind，作为AI领域的新星创业公司，MetaMind创办之初就拿了800万美元的风投，值得关注。

回到这们课程CS224d,其实可以翻译为“面向自然语言处理的深度学习（Deep Learning for Natural Language Processing）”，这门课程是面向斯坦福学生的校内课程，不过课程的相关材料都放到了网上，包括课程视频，课件，相关知识，预备知识，作业等等，相当齐备。课程大纲相当有章法和深度，从基础讲起，再讲到深度学习在NLP领域的具体应用，包括命名实体识别，机器翻译，句法分析器，情感分析等。Richard Socher此前在ACL 2012和NAACL 2013 做过一个Tutorial，Deep Learning for NLP (without Magic)，感兴趣的同学可以先参考一下: Deep Learning for NLP (without Magic) – ACL 2012 Tutorial – 相关视频及课件 。另外，由于这门课程的视频放在Youtube上，@爱可可-爱生活 老师维护了一个网盘链接：http://pan.baidu.com/s/1pJyrXaF ，同步更新相关资料，可以关注。

课程主页链接http://cs224d.stanford.edu/syllabus.html

3. coursera上面的Andrew NG的machine learning(https://www.coursera.org/learn/machine-learning)

以及

Geoffrey Hinton的nerual network used in Machine learning.(https://www.coursera.org/course/neuralnets)