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4.7K

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35

issues

#35・

An opportunity for you!

To focus on the projects we have in mind, we can only let a limited number of people join.We are starting with 1,000 spots of which 900 are currently available.The price of the membership raises for every 10 people that buy one. You have been putting up with …

 
#34・

Expanding your horizon

Probably the most used term in practical machine learning circles is "pipeline." Unfortunately, we use it to refer to different things at different times.Here is an overview of some of the different machine learning pipelines that you will find out there.

 
#33・

Start learning today

I started looking seriously into machine learning around the spring of 2015.Look around. Since that day, machine learning has turned the industry upside down.Here are some thoughts, some numbers, and some of the reasons you want to start with machine learning…

 
#32・

Training with all your data

Every day, I get many questions, most of them centered around building a machine learning career. I thought it was a good idea to collect some of the answers in a single place.

 
#31・

Don't look

Why would you?Test data should mimic production data. You don't have access to the latter, so why would you treat the former differently?

 
#30・

Do you need feature engineering?

Neural networks are powerful. Deep networks even more.Wouldn't these networks solve the problem of feature engineering? Aren't they capable of doing this for us?

 
#29・

The first neural network

1958.This is a story about the first neural network and the father of modern Deep Learning.It's when all started and suddenly stopped.And it's short.

 
#28・

Zero probability

Next Friday, I'll host a Twitter Space with 50 attendees.Tickets are on sale now. $2.99.You'll get to listen to me ramble about how you can build a career in Machine Learning. You will be able to ask questions.If you want to participate, click on the tweet be…