Your First Linear Regression Project in Python [Part 7] | Machine Learning for Beginners

📈🐍 In this tutorial, presented by Bea Stollnitz, a Principal Cloud Advocate at Microsoft, we'll guide you through creating your first linear regression project using Python and a toy dataset from scikit-learn. This video is part of our Machine Learning for Beginners series, where we'll cover various machine learning topics and their implementation using Python code in Jupyter notebooks.

In this video, you'll learn:

✅ How to load the diabetes dataset from scikit-learn
✅ How to extract and reshape the relevant data (BMI) for our regression model
✅ How to split the data into training and testing sets
✅ How to create and train a linear regression model using scikit-learn
✅ How to make predictions and evaluate the model's performance using matplotlib

If you're new to Jupyter notebooks and virtual environments, make sure to watch our previous video, where we walk you through setting up a Jupyter notebook with a virtual environment for data science projects.

Make sure to subscribe and hit the notification bell 🔔 so you won't miss our upcoming videos, where we'll dive deeper into various machine learning topics and guide you through their implementation using Python code in Jupyter notebooks. See you there!

📙 Follow along

#LinearRegression #Python #ScikitLearn #machinelearning #ml

📚 Learn more:

📇 Connect with Bea:

0:00 - Intro
0:21 - Open the Jupyter notebook from the ML for beginners repo
0:50 - The diabetes toy dataset from SciKit-Learn
1:36 - Load the diabetes dataset using the notebook
2:30 - Reshape numpy arrays to format the diabetes data
2:49 - Split data into train and test data sets
3:14 - Create and train a linear regression model, and make predictions
3:35 - Use matplotlib to visualize the predictions

[InsidiousIozan]

To everyone complaining that this is not beginner friendly, this is MACHINE LEARNING FOR BEGINNERS, not PYTHON FOR BEGINNERS. I recommend you familiarize yourself with python first before moving on to the complex topic of machine learning. If you get stuck on concepts like venv or have not worked with pandas, numpy and such, do learn a bit about them at least before starting this course.

[quilonconstruction]

Why all the attributes' values like age and sex a decimal value?

[SinethPriyasiri]

THis is too quick and how can a beginer understand these coding

[nikola]

I mean you should really do this on paper first like start from formula linear y = a + bx. How algorithm would work. I think it is important that we understand that first and not immediately type in code and use y_pred = model.predict(X_test). How you go on and fill in new data, do it all over again. Like you got single patient and you want to plug in just his bmi into the model and predict. Dont tell me you have to do it all over again?

[kamal-hassan]

This is not a beginner friendly! I think it'll be difficult to understand without prior knowledge to these frameworks (pandas, sklearn...) sadly :(

[hrkhrld]

IndexError: too many indices for array: array is 1-dimensional, but 2 were indexed

because of X = X[:, 2]

[methioswar]

Telling people what to do is not the same as teaching

[roryherman]

Ouch, that was not easy. The commands can be copied from the readme file located in in your folder.


I'm just a beginner, but the above worked (eventually). Hope it helps

[taiwosulaimon]

Well this isnt Beginners friendly. I dont even know where the pasted codes were gotten from. 🥲