Scikit-Learn Course - Machine Learning in Python Tutorial

Scikit-learn is a free software machine learning library for the Python programming language. Learn about machine learning using scikit-learn in this full course.

⭐️ Course Contents ⭐️

Chapter 1 - Getting Started with Machine Learning
⌨️ (0:00) Introduction
⌨️ (0:22) Installing SKlearn
⌨️ (3:37) Plot a Graph
⌨️ (7:33) Features and Labels_1
⌨️ (11:45) Save and Open a Model

Chapter 2 - Taking a look at some machine learning algorithms
⌨️ (13:47) Classification
⌨️ (17:28) Train Test Split
⌨️ (25:31) What is KNN
⌨️ (33:48) KNN Example
⌨️ (43:54) SVM Explained
⌨️ (51:11) SVM Example
⌨️ (57:46) Linear regression
⌨️ (1:07:49) Logistic vs linear regression
⌨️ (1:23:12) Kmeans and the math beind it
⌨️ (1:31:08) KMeans Example

Chapter 3 - Artificial Intelligence and the science behind It
⌨️ (1:42:02) Neural Network
⌨️ (1:56:03) Overfitting and Underfitting
⌨️ (2:03:05) Backpropagation
⌨️ (2:18:16) Cost Function and Gradient Descent
⌨️ (2:26:24) CNN
⌨️ (2:31:46) Handwritten Digits Recognizer

--

[haokang]

This video presents the basic logic behind several machine learning algorithms, neither too deep for a beginner nor too simple to skip through. Explanation and Examples, Theory and Codes. Perfect, if not the best!!! Thanks a lot!!!

[hemitpatel]

I have done 14 minutes of this course so far, it is amazing right now! He explains it really nicely keep up the good work man!!

[liranzaidman]

Great video.
3 comments please:
a. Use Pandas to make the results look like a nice readable table
b. In the linear regression, add also the p-values
c. In KNN and SVM show how to use the model for future data, not only the test part (i.e, how to implement it in SQL and/or BI program that is being refreshed daily).

[chrissmith]

important modules that was not included :

1. sklearn.ensemble
2. sklearn.feature_selection
3. sklearn.naive_bayes

But overall, this is a very good tutorial

[DatascienceConcepts]

This is extremely useful, especially for those who are new to data science and ML. Thanks!!

[augustvanhout]

I have a few months experience with Python, and this was a great tutorial for me. I'm now more ready to start on intermediate ML tutorials.

[googoogua]

Thanks!! 1:14:00.. the logit function... I think it should separate y from 0 [instead of 1]. If you consider z= e^-y, z would go from inf to 0, crossing 1 at y=0. So when y is negative, z gets bigger and bigger, and logit function would tend to 0; when y is positive, z gets closer and closer to 0, and logit function would tend to 1

[Harish-oudy]

32:08
instead of getting in to the file and adding the names of columns, one can use the following command

car_data = pd.read_csv('car.data', header = None)

car_data.columns = ['Buying', 'maint', 'doors', 'persons', 'lug_boots', 'safety', 'condition']

[celestialspecies]

These people need a salute for free service

[rahulranjan]

I was just hoping and it came in my notification. Thanks!!!

You are doing great service to community

[DiamondTech]

A perfect tutorial with no adds makes it more beautiful.

[chknise]

Great TUT!! Thanks for taking 3 hours out of your day to share this.

[mattm]

Thanks. I really enjoyed this! I found it helpful that there were some redundant parts. perfect pace for me.

[hazemalifareg]

Actually, I got frustrated as I 'm seeking for learning SKlearn from scartch, but unfortunately here the instructor is dealing with those having a pre-knowledge about the module and its components.

[pierreancelot]

@43:45 KNN Example, I believe a mistake is there. you should test against X, y but X_test, y_test instead. In X, y, you have a 80 percent chance to hit test values which will always be right, your test is wrong. if you use x_test and y_test, you'll see the model is not that good, after all, you have a 75% accuracy.

[tejasvix]

Damn i needed this sooo much rn and here you are

[STONEcreator]

Thank You! This was very helpful for me :)

[obinnaokafor]

Visual Studio Code is the best code editor/ IDE for anything Python. It provides an excellent support for Jupyter within the editor.

[lucasgonzalezsonnenberg]

`load_boston` has been removed from scikit-learn since version 1.2.

The Boston housing prices dataset has an ethical problem

[jerzysomkowski]

Overall this is good course however sci-kit learn is not only about algorithms. Ther's a ton of preprocessing modules, Pipelines, Model selection, and evaluation methods that I feel should be addressed.