Going with Scikit-Learn on Kaggle

Go to Kaggle with a bicycle-learner

Psych-learning has long been a popular library for beginners with machine learning. However, not everyone has the opportunity to use it yet. I will show you how to go cycling-learning along the short route, all you need is a web browser!

Brief history text

Let’s start for reference with a little dash of history. Psychit-Learn was originally called Psychits. Laren and David Cornepia began life as the Google Summer of Code project. The name 'Psychit' comes from the Saipan Toolkit.

Since then, psychic-learners have consistently embraced it and gained popularity today: a well-documented, well-documented Python machine learning library. If you take a look at scikit-learn.org, you will notice that the version number is quite low, 0.0 this as of this post. Don't be afraid of it; The library has been around for a long time and is well maintained and quite reliable.

What does a psychic learner do?

What's really neat about it is that it's a rich suite of tools that work "around machine learning", including everything from loading and manipulating equipment to pipelines and metrics. In my opinion, the really incredible aspect of Psych-Learning is the huge collection of machine learning algorithms that you can try, most of them with minimal code adjustments!

This is a really amazing way to get a handle on what different types of models do, as well as gain some insight around performing different parameters.

I created a simple Kaggle kernel using Psych-Learner to help you get started, and it also shows the interaction between the kernel and the datasets. Follow this brief video with each step as you walk through the kernel line.

If you are ready for a more sophisticated approach to using Kagal kernels and collaborating with others, check out this post to create data science projects at Kagal.

The next steps

This is just a simple view of how you can start socket-learning, but you will have to explore the vast world of machine learning models that psych-learner had to offer, with all the simple clean APIs! Open up tutorials and documents and create some amazing models.

Next time we'll talk about the other side of machine learning through psychic-learning - predictors, and how to measure it!

Scikit-learn website → https://scikit-learn.org