Machine Learning Entrepreneurship Applied Data Science

Machine Learning Entrepreneurship – Applied Data Science, available at $59.99, has an average rating of 4.8, with 21 lectures, based on 37 reviews, and has 265 subscribers.

You will learn about Learn how to transform your ML ideas into fully interactive web applications and paywall subscription sites This course is ideal for individuals who are Data scientists, python programmers, weekend entrepreneurs It is particularly useful for Data scientists, python programmers, weekend entrepreneurs.

Enroll now: Machine Learning Entrepreneurship – Applied Data Science

Summary

Title: Machine Learning Entrepreneurship – Applied Data Science

Price: $59.99

Average Rating: 4.8

Number of Lectures: 21

Number of Published Lectures: 20

Number of Curriculum Items: 21

Number of Published Curriculum Objects: 20

Original Price: $59.99

Quality Status: approved

Status: Live

What You Will Learn

Learn how to transform your ML ideas into fully interactive web applications and paywall subscription sites

Who Should Attend

Data scientists, python programmers, weekend entrepreneurs

Target Audiences

Data scientists, python programmers, weekend entrepreneurs

This class can be summarized in one sentence, “to learn how to put your machine learning ideas into your customer’s plate”. That’s it.

Here we will extend multiple Python machine learning ideas into fully interactive web applications, into a format that anybody anywhere can access as long as they have access to a web browser. Our last project will be built around a professional paywall infrastructure so you can control and monetize how and whom can access it.

Whether you want to test out business ideas or share advanced and predictive analytics ideas with the world, the tools taught in this class will allow you to do that quickly, easily and without spending a lot of money.

Course Curriculum

Chapter 1: Introduction

Lecture 1: What is Machine Learning Entrepreneurship?

Lecture 2: About me

Lecture 3: This is a master class – tools used in this class

Lecture 4: Hello World – Local Flask

Lecture 5: Hello World – PythonAnywhere

Chapter 2: Machine Learning Project 1 – Plagiarism Defender

Lecture 1: Exploring the Plagiarism Defender

Lecture 2: Building our local Flask web application

Lecture 3: Building our PythonAnywhere web application

Chapter 3: Machine Learning Project 2 – Predicting Earthquakes with Google Maps

Lecture 1: Exploring the earthquake predictor and visualizer – Part 1

Lecture 2: Exploring the earthquake predictor and visualizer Part 2

Lecture 3: Building our local Flask web application

Lecture 4: Building our PythonAnywhere web application

Chapter 4: Machine Learning Project 3.1 – Stock Market Trade Recommendations

Lecture 1: Exploring the Stock Market Trade Recommender – Part 1

Lecture 2: Exploring the Stock Market Trade Recommender – Part 2

Lecture 3: Exploring the Stock Market Trade Recommender – Part 3

Lecture 4: Building our local Flask web application

Lecture 5: Building our PythonAnywhere web application

Chapter 5: Machine Learning Project 3.2 – Building A Paywall

Lecture 1: Building the Memberful Paywall – Start Making Money on Your Content

Chapter 6: Bonus Material

Lecture 1: Quickly Build Great Looking Websites with Bootstrap and GitHub.io

Lecture 2: Create Your Own Free Email Signup Form for Static Web Sites

Instructors

Manuel Amunategui
Data Scientist & Quantitative Developer

Rating Distribution

1 stars: 0 votes

2 stars: 0 votes

3 stars: 2 votes

4 stars: 10 votes

5 stars: 25 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!