Searching on Google is one of the most important tasks in any development workflow. It's the central skill for anyone looking practice their coding skills in any development job, be it machine learning or otherwise.

In this article I want to share 9 tips for how to perform advanced google searches for machine learning

1. Searching machine learning papers after a certain date

site: arxiv.org machine learning after:2020

2. Searching papers that mention a specific word or sentence within a specific interval date

site: arxiv.org "artificial general intelligence 2019..2022"

3. Searching repositories that use a specific framework

site: github.com "pytorch" *& "RNN" after: 2020

4. Searching tools of a certain type

image annotation tool & "open source" after:2018

5. Searching Images of a Certain Size and Type

image:panda imagesize:256x256

6. Search social media & hashtags

@twitter transformers & #artificialintelligence

7. Search for a price of GPUs or Hardware in ML

GPU $600

8. Exclude topics from a search with "-" operator

Put - in front of a word you want to leave out. For example,

`"cloud provider" & "machine learning" -Azure -"Google Cloud" -AWS

(also search for without the exclude terms to show the difference)

Put "related:" in front of a web address you already know. For example,

related:kaggle.com

Other important operators:

  • filetype: to search specific file types
  • intitle: to search websites whose title contains a certain keyword
  • inurl: to search websites containing a certain search term in the url
  • intext: to search for websites containing a certain search term in the text
  • info: to find information about a specific page

Just Google It!

Any experienced developer in the machine learning field or anywhere else will tell you that for pretty much any task, question or concern you have: "Just google it!". Developing this skill is a must to boost your ability to self-learn complicated topics that require the combination of a lot of information.

Just google it!

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