AI速查表:神经网络、机器学习、深度学习与数据科学一览
本文是Chatbots Life创始人Stefan Kojouharov花费数学心血搜集的AI概念速查表,是学习神经网络、机器学习、深度学习与大数据必备之良方。
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1. 神经网络
2. 神经网络结构
3. 神经网络公式
4. 机器学习:概览
5. 机器学习:Scikit-learn算法
Scikit-learn是基于Python的功能强大的开源科学计算工具包,内含分类、回归、聚类、支持向量机、随机森林与Gradient Boosting等算法。
6. 机器学习:算法概览
7. Python数据科学
8. 大数据
9. TensorFlow
2017 年 5 月,谷歌宣布了第二代 TPU ,并在Google Compute Engine中加入了对 TPU 的支持。第二代 TPU 有高达 180 万亿次浮点运算性能。当 64 块TPU 组合使用时,可提供高达 11.5 千万亿次浮点运算的性能。
10. Keras
2017 年,TensorFlow核心库加入了对 Keras 的支持。Keras作者Chollet表示Keras更适合作端口使用,而非端对端的机器学习框架,它提供了更高级更直观的抽象集合,可轻松配置神经网络,无需考虑后端科学计算库。
11. NumPy
NumPy系统是Python的一种开源的数值计算扩展。这种工具可用来存储和处理大型矩阵,比Python自身的嵌套列表(nested list structure)结构要高效的多。
12. Pandas:Python结构化数据分析利器
13. Data Wrangling
14. Data Wrangling with dplyr and tidyr
15. SciPy
基于 NumPy 数组对象构建,是 NumPy 堆栈的一部分,包含 Matplotlib,pandas 和 SymPy 等工具,以及一个科学计算库的扩展集。
16. Matplotlib
Matplotlib是Python中常用的可视化工具之一,便于创建海量类型2D图表和一些基本的3D图表。
17. 数据可视化
18. PySpark
19. Big-O
速查表来源
Big-O Algorithm Cheat Sheet:
http://bigocheatsheet.com/
Bokeh Cheat Sheet:
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Bokeh_Cheat_Sheet.pdf
Data Science Cheat Sheet:
https://www.datacamp.com/community/tutorials/python-data-science-cheat-sheet-basics
Data Wrangling Cheat Sheet:
https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf
Data Wrangling:
https://en.wikipedia.org/wiki/Data_wrangling
Ggplot Cheat Sheet:
https://www.rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf
Keras Cheat Sheet:
https://www.datacamp.com/community/blog/keras-cheat-sheet#gs.DRKeNMs
Keras:
https://en.wikipedia.org/wiki/Keras
Machine Learning Cheat Sheet:
https://ai.icymi.email/new-machinelearning-cheat-sheet-by-emily-barry-abdsc/
Machine Learning Cheat Sheet:
https://docs.microsoft.com/en-in/azure/machine-learning/machine-learning-algorithm-cheat-sheet
ML Cheat Sheet:
http://peekaboo-vision.blogspot.com/2013/01/machine-learning-cheat-sheet-for-scikit.html
Matplotlib Cheat Sheet:
https://www.datacamp.com/community/blog/python-matplotlib-cheat-sheet#gs.uEKySpY
Matpotlib:
https://en.wikipedia.org/wiki/Matplotlib
Neural Networks Cheat Sheet:
http://www.asimovinstitute.org/neural-network-zoo/
Neural Networks Graph Cheat Sheet:
http://www.asimovinstitute.org/blog/
Neural Networks:
https://www.quora.com/Where-can-find-a-cheat-sheet-for-neural-network
Numpy Cheat Sheet:
https://www.datacamp.com/community/blog/python-numpy-cheat-sheet#gs.AK5ZBgE
NumPy:
https://en.wikipedia.org/wiki/NumPy
Pandas Cheat Sheet:
https://www.datacamp.com/community/blog/python-pandas-cheat-sheet#gs.oundfxM
Pandas:
https://en.wikipedia.org/wiki/Pandas_(software)
Pandas Cheat Sheet:
https://www.datacamp.com/community/blog/pandas-cheat-sheet-python#gs.HPFoRIc
Pyspark Cheat Sheet:
https://www.datacamp.com/community/blog/pyspark-cheat-sheet-python#gs.L=J1zxQ
Scikit Cheat Sheet:
https://www.datacamp.com/community/blog/scikit-learn-cheat-sheet
Scikit-learn:
https://en.wikipedia.org/wiki/Scikit-learn
Scikit-learn Cheat Sheet:
http://peekaboo-vision.blogspot.com/2013/01/machine-learning-cheat-sheet-for-scikit.html
Scipy Cheat Sheet:
https://www.datacamp.com/community/blog/python-scipy-cheat-sheet#gs.JDSg3OI
SciPy:
https://en.wikipedia.org/wiki/SciPy
TesorFlow Cheat Sheet:
https://www.altoros.com/tensorflow-cheat-sheet.html
Tensor Flow:
https://en.wikipedia.org/wiki/TensorFlow
原文地址:
https://becominghuman.ai/cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning-big-data-678c51b4b463
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