2.Moreparentheses.Inmachinelearning,authorsarepronetoomitparentheses,bracketsandbraces,thisusually causesambiguityinmathematicalformulas.Inthischeatsheet,Iuseparentheses(bracketsandbraces)atwhere theyareneeded,tomakeformulaseasytounderstand. 3.Lessthinkingjumps.Inmanybooks,authorsarepronetoomitsomestepsthataretrivial...
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software architecture design,windows kernel/CLR debugging skills,SQL Server 、MySQL,Database architecture、Query Optimization、troubleshooting and high availability, parallel/multi-threaing programming,distributed computing,cloud computing ,Apache Storm, Spark, Flink,Machine Learning, Deep Learning ,TensorFlow an...
Also, learning something with a purpose in mind is much more appealing than going through pages and pages of formulas and code without any underlying reason for doing so. In a nutshell: Learning implementing a side project is much more fun and quick! What do you think about it? I’d ...
learning Python seemed to be the trend, and without it, one was not considered competent in data processing. Nowadays, with data visualization being the buzzword, most Excel users have to search for tutorials online and learn on the spot for unfamiliar formulas. Complex operations often require ...
formulaic An implementation of Wilkinson formulas. 12 itemadapter Common interface for data container classes 12 weaviate-client A python native weaviate client 12 heapdict a heap with decrease-key and increase-key operations 12 gplearn Genetic Programming in Python, with a scikit-learn inspired API...
Kirill Eremenko joins Jon Krohn for another exclusive, in-depth teaser for a new course just released on the SuperDataScience platform, “Machine Learning Level 2”. Kirill walks listeners through why decision trees and random forests are fruitful for bu
(Y) X Y = A − mXX1 (,YXY)=2m2 m1 (Y) ( , XA)m=2 (Y ∅ ) , A (10) Stacking is widely used Xin∩vYar=io∅us machine learning competitions and has a excSittianckginrgesius wltsidienlyinusteedgrinatvianrgiodusifmfearcehnintem...
Python and R cheat sheets for machine learning algorithms. It contains codes on data science topics, decision trees, random forest, gradient boost, k means.