Part one
No 1. 《机器学习有很多关于核函数的说法，核函数的定义和作用是什么？ - 知乎》
http://weibo.com/1402400261/E9oLJtdUe
No 2. 《用Python写网络爬虫》
http://weibo.com/1402400261/E9oIKuVlZ
No 3. 【30大免费爬虫组件/软件/服务】
http://weibo.com/1402400261/E9ouVxNz6
No 4. 《Face Detection with End-to-End Integration of a ConvNet and a 3D Model》
http://weibo.com/1402400261/E9oO4zG6U
No 5. 【博弈论在线(视频)】
http://weibo.com/1402400261/E9l3mhZBl
No 6. 【(R)非平衡类机器学习实例】
http://weibo.com/1402400261/E9kb4kvMi
No 7. 【SVM简明概述】
http://weibo.com/1402400261/E9otg9XT8
No 8. 【深度学习失败案例】
http://weibo.com/1402400261/E9kW0CSmw
No 9. 如何使用本书(写在第十次印刷之际) http://t.cn/RGqEgwT ，PDF ( http:...
http://weibo.com/1402400261/E9jpICpvD
No 10. 《基于骨架的机器翻译》
http://weibo.com/1402400261/E9pQ4pYdv
No 11. 《最前沿：深度增强学习再发力，家用机器人已近在眼前》
http://weibo.com/1402400261/E9kCo5tpa
No 12. 《Deep Learning Cuts Error Rate for Breast Cancer Diagnosis | NVIDIA Blog》
http://weibo.com/1402400261/E9pzyfQ5V
No 13. 【Python股市数据分析教程】
http://weibo.com/1402400261/E9kR1elPn
No 14. 【理解图像分类/机器学习中的正则化】
http://weibo.com/1402400261/E9ksQfvLQ
No 15. 【(TensorFlow)基于LSTM的歌词自动生成】
http://weibo.com/1402400261/E9pw4fwEl
No 16. 《机器学习模型选择如此简单》
http://weibo.com/1402400261/E9tr8DrMV
No 17. 【Python自然语言处理】
http://weibo.com/1402400261/E9kpylKYt
No 18. 【Nvidia使用的TensorFlow实战教程】
http://weibo.com/1402400261/E9o7joJql
No 19. “CSDN技术主题月----“深度学习”代码笔记专栏” http://t.cn/RcOsq9h...
http://weibo.com/1402400261/E9tsUzCox
No 20. 《技术揭秘：海康威视PASCAL VOC2012目标检测权威评测夺冠之道》
http://weibo.com/1402400261/E9k9biATT
No 21. 《如何通俗易懂地介绍 Gaussian Process？ - 知乎》
http://weibo.com/1402400261/E9g6s5YOp
No 22. 【数据科学维恩图之争】
http://weibo.com/1402400261/E9osAvkJZ
No 23. 【多伦多大学新课：可微推理与生成模型】
http://weibo.com/1402400261/E9pGQ3mHy
No 24. 【Python科学计算资源汇总】
http://weibo.com/1402400261/E9rgWsDNc
No 25. 【向TensorFlow进军】
http://weibo.com/1402400261/E9twLkCYw
No 26. 《深度学习即将攻陷的下一个领域：NLP——ACL2016优秀论文解读》
http://weibo.com/1402400261/E9rjQpBsQ
No 27. 《Learning Robust Representations of Text》
http://weibo.com/1402400261/E9oEg8FUV
No 28. 【超酷的“几何基元”图片风格(Go语言)】
http://weibo.com/1402400261/E9kodi0wL
No 29. 《深度学习 之 Sequence Learning》
http://weibo.com/1402400261/E9rmP8RR8
No 30. 【概率论与统计应用】
http://weibo.com/1402400261/E9krtoert
No 31. 转发微博//如何使用本书(写在第十次印刷之际) http://t.cn/RGqEgwT ，PDF (...
http://weibo.com/1402400261/E9jpICpvD
No 32. 《开源人脸识别seetaface入门教程》
http://weibo.com/1402400261/E9tjz7X9c
No 33. 《SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient》
http://weibo.com/1402400261/E9hN47jAx
No 34. 【CNN之Attention】
http://weibo.com/1402400261/E9to94aDS
No 35. 【人工神经网络】
http://weibo.com/1402400261/E9ow9fdeA
No 36. 帮转支持//我今天打电话给清华大学出版社，预计这周末会印制出来。我大概可以先期拿到120本，并计划在...
http://weibo.com/1402400261/E9q2OkoKU
No 37. 【如何处理无法载入内存的大型数据集】
http://weibo.com/1402400261/E9tC2pdrJ
No 38. 【用计算机技术治愈癌症】
http://weibo.com/1402400261/E9l4QaEBl
No 39. 【句子表示与问题应答】
http://weibo.com/1402400261/E9ojnBdDB
No 40. 'Everyone's favourite co-author' via:Arvid Ågren h...
http://weibo.com/1402400261/E9f6f1B5c
No 41. 【高基数特征如何处理】
http://weibo.com/1402400261/E9oojqCv2
No 42. 【深度(梦幻)机使用篇】
http://weibo.com/1402400261/E9t7e8IZB
No 43. 《深度学习系统相比较传统的机器学习系统，针对常见的分类问题，精度究竟能有多大提升？ - 知乎》
http://weibo.com/1402400261/E9kBKeFbU
No 44. 《Variational Autoencoder for Deep Learning of Images, Labels and Captions》
http://weibo.com/1402400261/E9oKzDIAn
No 45. 【Google Trips里280年历史的经典算法】
http://weibo.com/1402400261/E9jooe260
No 46. 有关机器阅读理解的文本表示部分：'机器阅读理解中文章和问题的深度学习表示方法 ' http://t....
http://weibo.com/1402400261/E9l5NfXww
No 47. 《哪些 Python 库让你相见恨晚？ - 知乎》
http://weibo.com/1402400261/E9g5cCKtW
No 48. 【(torch7)基于Warp-CTC的DeepSpeech2语音识别】
http://weibo.com/1402400261/E9pt2Cg9g
No 49. 《Hierarchical Multiscale Recurrent Neural Networks》
http://weibo.com/1402400261/E9pp53pXg
No 50. '机器阅读理解中文章和问题的深度学习表示方法'//有关机器阅读理解的文本表示部分：'机器阅读理解中文...
http://weibo.com/1402400261/E9l5NfXww
Part Two
Step 1: Basic Python Skills
▪ Python The Hard Way by Zed A. Shaw
▪ Google Developers Python Course (highly recommended for visual learners)
▪ An Introduction to Python for Scientific Computing (from UCSB Engineering)by M. Scott Shell (a great scientific Python intro ~60 pages)
▪ Learn X in Y Minutes (X = Python)
Step 2: Foundational Machine Learning Skills
▪ Unofficial Andrew Ng course notes
▪ Tom Mitchell Machine Learning Lectures
Step 3: Scientific Python Packages Overview
▪ numpy – mainly useful for its N-dimensional array objects
▪ pandas – Python data analysis library, including structures such as dataframes
▪ matplotlib – 2D plotting library producing publication quality figures
▪ scikit-learn – the machine learning algorithms used for data analysis and data mining tasks ▪ Scipy Lecture Notes by Gaël Varoquaux, Emmanuelle Gouillart, and Olav Vahtras
▪ 10 Minutes to Pandas
Step 4: Getting Started with Machine Learning in Python
▪ iPython Notebook Overview from Stanford
▪ An Introduction to scikit-learn by Jake VanderPlas
▪ Example Machine Learning Notebook by Randal Olson
▪ Model Evaluation by Kevin Markham
Step 5: Machine Learning Topics with Python
▪ k-means Clustering by Jake VanderPlas
▪ Decision Trees via The Grimm Scientist
▪ Linear Regression by Jake VanderPlas
▪ Logistic Regression by Kevin Markham
Step 6: Advanced Machine Learning Topics with Python
▪ Support Vector Machines by Jake VanderPlas
▪ Kaggle Titanic Competition (with Random Forests) by Donne Martin
▪ Dimensionality Reduction by Jake VanderPlas
Step 7: Deep Learning in Python
▪ Neural Networks and Deep Learning by Michael Nielsen
▪ Theano Deep Learning Tutorial by Colin Raffel
▪ Dreaming Deep with Caffe via Google’s GitHub
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