How to Prepare Data for Machine Learning and A.I.

In this video, Alina discusses how to prepare data for Machine Learning and AI. Artificial Intelligence is only as powerful as the quality of the data collection, so it's important to prepare data for Machine learning correctly to ensure no data bias in the prediction models.

We received a lot of questions about how much data someone needs to run a prediction model for a business, and how to avoid common mistakes in data collection for AI. The answer is you don't need big-data to run AI models and Machine learning models, it can be done with ‘medium-data’!

It's also important to be careful with the quality of data collected for Machine learning and AI. Marketers must be careful, all the data that we collect for machine learning models can be subject to bias. This bias can fall into many categories, two common ones are selection bias and exclusion bias. And both types can affect the usability and relevance of your AI models and findings.

Selection bias is when the group of users used for data collection is not like your target audience. Exclusion bias is when you've already collected your data, but you hold back bits of your information from your analysis.

Artificial Intelligence reveals unexpected insights and good data collection is driven by knowing we're all subject to bias. So instead of only feeding a subset of your data to a machine learning model, dump it all in. Even the stuff you think is irrelevant. If it's irrelevant, the algorithm will ignore it.

Just remember:

- You don't need big data when you prepare data for machines learning & A.I. , you only need medium data.
- Make sure that you try to avoid bias as much as possible when you collect data for A.I.

This video covers:

Artificial intelligence in business
Data collection for A.I.
Machine Learning Data Bias
Big Data
AI tools
Selection bias
Exclusion bias
Prediction model bias
Machine learning
Artificial intelligence
Algorithmic bias
Preparing data for machine learning
Machine learning models
Preparing AI datasets

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[Camielroex]

Recognizable problem explained really well. Thanks!

[ThePol]

I’ve learn something today, thanks to this video! And that’s amazing!!!

[tatsuyakohrogi]

I like how simple and clear this video is!

[leonardoubbiali]

Great video. Thanks for the huge value guys!

[bernardofn]

Always keeping it scientifically rigorous + w/ insightful analogies!

[nomad]

Thank you so much informative videos. What kinda of tool can we use with Google analytics data?

[ltsgroupcompany]

helpful video!! Good content! thanks :)

[ivotanku]

Best explanation to what seems a complex problem for many to grasp.

[akramsystems]

Im just wondering wouldn't there be weighting biases depending on the amount of data you have for one category vs another category i.e. you have 100 records for one category and 10000 records for another category?

[guillermoalcantaragonzalez]

Would it be better to make a random/stratified selection of the data?

[norpriest]

This is Inbound Marketing at best.
You're trying to put out useful stories rather than pushing or forcing contents on people.
You're on the right path.

[ahmedshenawy]

Thanks for video, and the instructor is very pretty by the way 😂❤❤

[GeorgeVivanco]

Am new to the AI world and would like to know what AI software should I be look at. I have a landing page on my website and sell upgrades to services provided. I have about 2500 clients and would like to use past purchased to see what offers are best and if I should create other offers.

[moisesf.]

your big data concept is different to actual big data concept (5 v)

[amiryavariabdi]

Dear the artificial intelligence community
I am pleased to introduce DIDA dataset, which is the largest handwritten digit dataset. I will be grateful, if you could help me to introduce this dataset to the community.
Thanks

[lawrencetaulk]

Wow, a beautiful girl and a wonderful lecture.

[agustriberry]

What is her sosmed? 😂, she so attractive on this vid

[natanbolin]

why after the last sentence all i could think of is "I am the AI"!?

[flymvyr]

с таким акцентом лучше по-руски рассказыать