Hands-On Machine Learning with scikit-learn and Python

Name: Hands-On Machine Learning with scikit-learn and Python
Rating: 3.6 (100 reviews)

A practical approach

(100 ratings)

15,449 students

Created by Cristi Zot

Last updated 1/2020

English

English [Auto]

30-Day Money-Back Guarantee

What you'll learn

Machine Learning with scikit-learn and Python

Requirements

Python programming
Basic math knowledge or willingness to learn fast

Description

You keep hearing about machine learning and artificial intelligence and how they revolutionize the world we live in. You want to learn more. You're in the right place.

You have basic understanding of Python and you are decent in math. Better!

You're going to learn hands-on machine learning with scikit-learn, a Python library for machine learning. Since this is a hands-on course, you will be working your way through with Python and Jupyter notebooks.

Who this course is for:

You want to get into machine learning and artificial intelligence
You already work in ML/AI and need to learn to program basic algorithms in Python with scikit-learn
You are a student, know a bit of coding, and want to get into ML/AI
You are a programmer and want to smoothly transition into ML/AI

8 sections • 44 lectures • 3h 53m total length

Preview01:24
Machine Learning with Scikit-Learn - Part 2
04:41
Machine Learning with Scikit-Learn - Part 3
05:23
Machine Learning with Scikit-Learn - Part 4 - Process Outline
03:38

Preview05:06
Machine Learning with Scikit-Learn - Part 20 - Neural Networks 2
03:53
Machine Learning with Scikit-Learn - Part 21 - Neural Networks 3
06:26
Machine Learning with Scikit-Learn - Part 22 - Neural Networks 4
05:32
Machine Learning with Scikit-Learn - Part 23 - Neural Networks 5
05:38
Machine Learning with Scikit-Learn - Part 24 - Neural Networks 6
03:19

Machine Learning with Scikit-Learn - Part 25 - SVMs 1
04:34
Machine Learning with Scikit-Learn - Part 26 - SVMs 2
05:15
Machine Learning with Scikit-Learn - Part 27 - SVMs 3
04:12
Machine Learning with Scikit-Learn - Part 28 - SVMs 4
03:42
Machine Learning with Scikit-Learn - Part 29 - SVMs 5
05:57
Machine Learning with Scikit-Learn - Part 30 - SVMs 6
02:48
Machine Learning with Scikit-Learn - Part 31 - SVMs 7
03:38

Machine Learning with Scikit-Learn - Part 32 - The Decision Function
05:43
Machine Learning with Scikit-Learn - Part 33 - Predict Proba
05:28
Machine Learning with Scikit-Learn - Part 34 - Uncertainty Estimation
07:28
Machine Learning with Scikit-Learn - Part 35 - Preprocessing - Binarization
06:55
Machine Learning with Scikit-Learn - Part 36 - Preprocessing - Mean Removal
04:07
Preview03:05
Machine Learning with Scikit-Learn - Part 38 - Preprocessing - Normalization
04:16
Machine Learning with Scikit-Learn - Part 39 - Preprocessing - Label Encoding
06:22
Machine Learning with Scikit-Learn - Part 40 - One Hot Encoding 1
06:28
Machine Learning with Scikit-Learn - Part 41 - One Hot Encoding 2
04:14
Machine Learning with Scikit-Learn - Part 42 - Automatic Feature Selection 1
07:51
Machine Learning with Scikit-Learn - Part 43 - Automatic Feature Selection 2
06:16
Machine Learning with Scikit-Learn - Part 44 - Automatic Feature Selection 3
07:43

Cristi Zot

Cybersecurity Researcher | Machine Learning Enthusiast

4.2 Instructor Rating
2,268 Reviews
116,915 Students
7 Courses

I’m Cristi. I hold an MS in Civil Engineering and I work as a Cybersecurity Analyst. I've got my Offensive Certified Security Professional Certification a couple of months ago.

Machine learning and AI are currently on my high interests as well and I am looking to combine ML/AI with cybersecurity at some point in the future.

Hands-On Machine Learning with scikit-learn and Python

What you'll learn

Requirements

Description

Who this course is for:

Course content

Introduction4 lectures • 15min

KNN - K-Nearest Neighbors3 lectures • 18min

Logistic Regression3 lectures • 24min

Decision Trees5 lectures • 25min

Random Forests3 lectures • 16min

Neural Networks6 lectures • 30min

Support Vector Machines7 lectures • 30min

Preprocessing and other Techniques13 lectures • 1hr 16min

Instructor