Kaggle 30 Days of ML - Day 9 - Build first ML Model, Validation - Learn Python ML in 30 Days

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This is the Day 9 of Kaggle's 30 Days of ML Challenge where you can learn Machine Learning (based on Python) in 30 days (Kind of). It's not a competition but a challenge to make a habit of coding ML every day. If you haven't registered for the Kaggle Challenge Don't worry, You can follow along my videos every day.

From Kaggle Email:

💡 What You’ll Learn
In Lesson 3 (Your First Machine Learning Model), you’ll create a machine learning model using the scikit-learn library, one of the most popular and efficient tools for data analysis.

Along the way, you’ll learn some basic techniques for working with very large datasets. These skills are especially important for modern data scientists, who often work with “big data” containing millions of variables ― many more than a human can conceivably understand! Thankfully, machines excel at discovering useful patterns in datasets that are too large for humans to wrap their heads around. :)

Once you have built a model, how good is it? How exactly should you judge how close the model’s predictions are to what actually happened? In Lesson 4 (Model Validation), you’ll use model validation to measure the quality of your model.

Exercise 2(from Lesson 4 of the Intro to ML course) -

Courtesy: Kaggle Learn

Related Videos:

Kaggle Introduction Walkthrough to get you started with Data Science - Webinar
#kaggle #30daysofml #machinelearning #datascience

1littlecoder

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Thank you so much .. your explanation is very easy to understand.

kmanju

Thanks for the it’s a great help for beginners and all alike

kumudksingh

Is their any deadline to complete this

tanishaagarwal

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