Machine Learning Intro for Python Developers

Machine Learning Intro for Python Developers, available at $39.99, has an average rating of 4.22, with 19 lectures, based on 176 reviews, and has 22820 subscribers.

You will learn about Machine Learning Basics with Python How to apply ML algorithms to your own problems How some algorithms work internally (kmeans, decision tree) Classify data automatically Predict prices with algorithms Group data points automatically This course is ideal for individuals who are Python developers curious about Machine Learning It is particularly useful for Python developers curious about Machine Learning.

Enroll now: Machine Learning Intro for Python Developers

Summary

Title: Machine Learning Intro for Python Developers

Price: $39.99

Average Rating: 4.22

Number of Lectures: 19

Number of Published Lectures: 19

Number of Curriculum Items: 19

Number of Published Curriculum Objects: 19

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Machine Learning Basics with Python
How to apply ML algorithms to your own problems
How some algorithms work internally (kmeans, decision tree)
Classify data automatically
Predict prices with algorithms
Group data points automatically

Who Should Attend

Python developers curious about Machine Learning

Target Audiences

Python developers curious about Machine Learning

Learn how to use Machine Learning with Python Scikit!

This is a getting started course for Machine Learning. If you are new to Machine Learning, this course is for you!

We’ll teach you how to get started with Machine Learning including these topics:

What is Machine Learning
Automatically classify new data
Predict prices with regression
Group your data automatically with clustering

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: What is Machine Learning?

Lecture 3: Example Problems

Lecture 4: Supervised Learning

Chapter 2: First Program (Classifier)

Lecture 1: Installing Scikit and Numpy

Lecture 2: Important Note

Lecture 3: First Program (Classifier)

Lecture 4: Lecture Notes

Lecture 5: Exercise

Chapter 3: Iris Classifier

Lecture 1: Iris Classifier

Lecture 2: Accuracy Score

Lecture 3: See a Decision Tree

Chapter 4: Regression

Lecture 1: Linear Regression

Lecture 2: Lecture Notes

Lecture 3: Regression Example

Lecture 4: Polynomial Regression

Chapter 5: Clustering

Lecture 1: Clustering

Lecture 2: Lecture Notes

Lecture 3: Kmeans explained

Instructors

Frank Anemaet
Supercharge Your Career

Rating Distribution

1 stars: 5 votes
2 stars: 13 votes
3 stars: 32 votes
4 stars: 53 votes
5 stars: 73 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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