文的自动分类 半监督学习 - 介于监督学习和无监督学习之间，算法: Graph Inference 或者Laplacian SVM 强化学习- 通过观察来学习做成如何的动作, 算法：Q-Learning以及时间差学习 机器学习－ 方法及流程 输入特征选择 – 基于什么进行预测 目标 – 预测什么 预测功能 – 回归、聚类、降维... Xn -> F(xn) -> T(x) 机器学习－ (NYU,2002), Facebook AI, Google Deepmind Theano (University of Montreal, ~2010), 学院派 Kersa, “Deep Learning library for Theano and TensorFlow” Caffe (Berkeley)，卷积神经网络,贾扬清 TensorFlow (Google) Spark MLLib

Data + Machine Learning[R1] + Powerful Computation[R2] • 完全意义上的自下而上的方式 • 从海量的数据中去挖掘异构、动态、碎片化的知识 e.g., 从Web corpora、搜索日志等都可挖掘出有价值的知识 R1, http://www.erogol.com/brief-history-machine- learning/ R2, https://openai Pipeline of Knowledge Graph Construction by Data-driven manner Figure 1: Data-driven KG construction techniques 刘峤，李杨等人, 知识图谱构建技术综述, 计算机研究与发展, 53 (3)，2016  Data acquisition • 结构化的数据（工业界常用） • 半结构化的数据（工业界常用）

don’t want to read lots of documentation before getting started, here are some pointers to quick learning resources: • Read the mypy cheatsheet. • Read Using mypy with an existing codebase if you have 56 Chapter 1. Contents Mypy Documentation, Release 1.8.0 You can use different type narrowing techniques to narrow object to a more specific type (subtype) such as int. Type narrowing is not needed with (values with type Any). 1.11 Type narrowing This section is dedicated to several type narrowing techniques which are supported by mypy. Type narrowing is when you convince a type checker that a broader

other words, it means functionally directed towards modelling objects. This is one of the many techniques used for modelling complex systems by describing a collection of interacting objects via their Python environment on your local computer. Prerequisites and Toolkits Before you proceed with learning further on Python, we suggest you to check whether the following prerequisites are met:  13 Screenshot Choosing a Text Editor You may not always need an IDE. For tasks such as learning to code with Python or Arduino, or when working on a quick script in shell script to help you automate

don’t want to read lots of documentation before getting started, here are some pointers to quick learning resources: Read the mypy cheatsheet. Read Using mypy with an existing codebase if you have a significant switch to using Any if you get a type checker complaint. You can use different type narrowing techniques to narrow object [https://docs.python.org/3/library/functions.html#object] to a more specific type values (values with type Any). Type narrowing This section is dedicated to several type narrowing techniques which are supported by mypy. Type narrowing is when you convince a type checker that a broader

don’t want to read lots of documentation before getting started, here are some pointers to quick learning resources: Read the mypy cheatsheet. Read Using mypy with an existing codebase if you have a significant switch to using Any if you get a type checker complaint. You can use different type narrowing techniques to narrow object [https://docs.python.org/3/library/functions.html#object] to a more specific type values (values with type Any). Type narrowing This section is dedicated to several type narrowing techniques which are supported by mypy. Type narrowing is when you convince a type checker that a broader

don’t want to read lots of documentation before getting started, here are some pointers to quick learning resources: • Read the mypy cheatsheet. • Read Using mypy with an existing codebase if you have switch to using Any if you get a type checker complaint. You can use different type narrowing techniques to narrow object to a more specific type (subtype) such as int. Type narrowing is not needed with (values with type Any). 1.11 Type narrowing This section is dedicated to several type narrowing techniques which are supported by mypy. Type narrowing is when you convince a type checker that a broader

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 1.11 Performance Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 1.12 Transactions == join_query.c.id # Becomes: (t1."parent_id" = "jq"."id") 1.11 Performance Techniques This section outlines some techniques for improving performance when using peewee. 1.11.1 Avoiding N+1 queries The optimizations employed by the database when joining or executing a subquery. 1.11. Performance Techniques 105 peewee Documentation, Release 3.3.0 Peewee provides several APIs for mitigating N+1 query

Keys Traversing foreign keys Joining tables Implementing Many to Many Self-joins Performance Techniques Avoiding N+1 queries Iterating over lots of rows Speeding up Bulk Inserts Transactions Context parent == join_query.c.id # Becomes: (t1."parent_id" = "jq"."id") Performance Techniques This section outlines some techniques for improving performance when using peewee. Avoiding N+1 queries The term query. Note.delete().where(Note.person_id.in_(foo_people)).execute() More If you’re interested in learning more, check out the project source code [https://github.com/coleifer/peewee]. Hacks Collected

pragmas=(('foreign_keys', 'on'),) when you instantiate SqliteDatabase. Performing simple joins As an exercise in learning how to perform joins with Peewee, let’s write a query to print out all the tweets by “huey”. To classes used to describe a SQL AST, see the query builder API documentation. If you’re interested in learning more, you can also check out the project source code [https://github.com/coleifer/peewee]. Hacks group. For a thorough discuss of various techniques, check out my blog post Querying the top item by group with Peewee ORM [http://charlesleifer.com/blog/techniques-for-querying-lists-of- objects-and-de