HomeCoursesHands-on Machine Learning with Scikit-Learn

Intermediate

Updated 5 months ago

Hands-on Machine Learning with Scikit-Learn
Save

Gain insights into Scikit-Learn's datasets, feature engineering, linear/logistic regression, and unsupervised learning. Delve into k-means clustering and neural networks to enhance your machine learning expertise.

Join 2.7 million developers at

Overview

Content

Reviews

Scikit-Learn is a powerful library that provides a handful of supervised and unsupervised learning algorithms. If you’re serious about having a career in machine learning, then scikit-learn is a must know. In this course, you will start by learning the various built-in datasets that scikit-learn offers, such as iris and mnist. You will then learn about feature engineering and more specifically, feature selection, feature extraction, and dimension reduction. In the latter half of the course, you will dive into linear and logistic regression where you’ll work through a few challenges to test your understanding. Lastly, you will focus on unsupervised learning and deep learning where you’ll get into k-means clustering and neural networks. By the end of this course, you will have a great new skill to add to your resume, and you’ll be ready to start working on your own projects that will utilize scikit-learn.

Scikit-Learn is a powerful library that provides a handful of supervised and unsupervised learning algorithms. If you’re serious...Show More

Content

36 Lessons2 Quizzes5 Challenges

Preliminaries

2 Lessons

Get familiar with Scikit-learn, its tools, practical use, and required prerequisites.

Introduction

Prerequisites

Working with Datasets

3 Lessons

Get started with loading datasets, generating synthetic data, and essential data preprocessing techniques.

Load built-in dataset

Generate synthetic dataset

Data Preprocessing

Feature Engineering

5 Lessons

Go hands-on with feature selection, extraction, missing value handling, PCA, and pipelines.

Feature Selection

Feature Extraction

Missing Value

PCA(Principal Component Analysis)

Pipeline

General Concepts

3 Lessons

Break down complex ideas of metrics selection and parameter searching for machine learning.

Metrics

Parameter Searching

Quiz

Linear Regression

3 Lessons

Solve problems in building and evaluating linear regression models using Scikit-Learn.

Linear Regression

Challenge - Auto Insurance Prediction

Challenge Solution Review

Logistic Regression

3 Lessons

Tackle logistic regression, preprocess data, and evaluate binary classification models.

Logistic Regression

Challenge - Classification Prediction With Data Preprocessing

Challenge Solution Review

Support Vector Machine

3 Lessons

Practice using SVMs for classifying both linear and non-linear data effectively.

Support Vector Machine

Challenge - Classification of non-linear data

Challenge Solution Review

Tree Model and Ensemble Method

5 Lessons

Step through decision trees, gradient boosting, parameter tuning, and random forest models using Scikit-Learn.

Decision Tree

Gradient Boosting Tree

Challenge - GBDT Parameter Fine-Tune

Challenge Solution Review

Random Forest

Unsupervised Learning

2 Lessons

Look at key unsupervised learning techniques: K-means clustering and t-SNE for data visualization.

K-means Clustering

t-SNE

10.

Deep Learning

3 Lessons

Go hands-on with building and fine-tuning neural networks using Scikit-Learn's MLPClassifier.

Neural Network

Challenge - Build a Neural Network and fine-tune it

Challenge Solution Review

11.

Others

3 Lessons

Apply your skills to Naive Bayes classifiers and K-Nearest Neighbors for predictive modeling.

Naive Bayes

KNN (K-Nearest Neighbors)

Quiz

12.

What's Next

1 Lessons

Deepen your knowledge of next steps in AI and recommended learning resources.

Where to Next?

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Neko Yan

Developed by MAANG Engineers

Every Educative resource is designed by our team of ex-MAANG software engineers and PhD computer science educators — subject matter experts who’ve shipped production code at scale and taught the theory behind it. The goal is to get you hands-on with the skills you need to stay ahead in today's constantly evolving tech landscape. No videos, no fluff — just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

Trusted by 2.7 million developers working at companies

"These are high-quality courses. Trust me. I own around 10 and the price is worth it for the content quality. EducativeInc came at the right time in my career. I'm understanding topics better than with any book or online video tutorial I've done. Truly made for developers. Thanks"

Anthony Walker

@_webarchitect_

"Just finished my first full #ML course: Machine learning for Software Engineers from Educative, Inc. ... Highly recommend!"

Evan Dunbar

ML Engineer

"You guys are the gold standard of crash-courses... Narrow enough that it doesn't need years of study or a full blown book to get the gist, but broad enough that an afternoon of Googling doesn't cut it."

Carlos Matias La Borde

Software Developer

"I spend my days and nights on Educative. It is indispensable. It is such a unique and reader-friendly site"

Souvik Kundu

Front-end Developer

"Your courses are simply awesome, the depth they go into and the breadth of coverage is so good that I don't have to refer to 10 different websites looking for interview topics and content."

Vinay Krishnaiah

Software Developer

"I've tried probably 5-7 different sites and Educative is easily the best. It perfectly blends explanation with interactivity"

Eric Downs

Musician/Entrepeneur

Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Instant Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

AI Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

Adaptive Learning

At various checkpoints throughout Educative courses, you will be prompted to take a quick assessment. Receive a condensed curriculum tailored to your strengths and skill gaps.

Explain with AI

Select any text within any Educative course, and get an instant explanation — without ever leaving your browser.

AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

Course

Algorithms for Coding Interviews in Python

Your ultimate guide to algorithms for coding interviews. Master several must-know algorithms, and test your skills with real-world problems from top companies.

15 h

intermediate

Course

Machine Learning System Design

Gain insights into ML system design, state-of-the-art techniques, and best practices for scalable production. Learn from top researchers and stand out in your next ML interview.

1 h 30 m

intermediate

Course

Grokking the Machine Learning Interview

Your proven path to success in Machine Learning Interviews – developed by FAANG engineers. Unlock ML loops at top companies with a System Design approach.

15 h

intermediate

Course

Python Quickstart for Experienced Programmers

This course provides a quick Python overview. It is for experienced programmers looking for key Python essentials to get productive quickly.

1 h 30 m

intermediate

Course

Matplotlib for Python: Visually Represent Data with Plots

Gain insights into visually representing data with Matplotlib in Python. Explore plotting techniques, control axes, create complex layouts, and draw various plots, enhancing your data science skills.

6 h

intermediate

Course

Python for Scientists and Engineers

Gain insights into Python for scientific computing. Explore arrays, plotting, linear equations, and algorithms using NumPy, Matplotlib, SciPy. Delve into applying tools with practical exercises.

13 h

intermediate

Cloud Lab

Speech Synthesis Using Amazon Polly

Learn to use Amazon Polly for text-to-speech synthesis, integrating SSML for natural speech effects and enhancing applications.

1 h

beginner

Course

Algorithms for Coding Interviews in Python

intermediate

15 hour

Course