Python learning memo for machine learning by Chainer Chapters 1 and 2

What This is an article that summarizes what I noticed and researched when learning machine learning using Chainer. It is written based on my understanding, so it may be incorrect. I will correct any mistakes.

Content

1. Introduction Notes on

Jupiter Notebook It looks like the original development environment. It is provided by Google Colaboratory, one of the cloud services. It seems to work on the browser.

runtime

It refers to the timing of executing the program. Here, it seems to show the elapsed time from the execution of the program.

2. Notes on getting started with Python

division

The return value will always be a float type Multiplication is possible for string type. Repeated output

Comparison operator

The return value is bool type exa. Type (1 <2) => true

Escape sequence

Line break \ n, tab \ t * Valid for print () function

String conversion method

There is a method to uppercase or lowercase. Variable str can be converted with str.upper (), str.lower ()

String insertion method

There is a method that allows you to insert a string into a string. .format ()

List (array)

There is a way to refer from the end instead of the beginning, the last specifies [-1] for the index, returns [-2], [-3] Apparently there are a lot of features related to this list, so I will turn it next time

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