Your 1st Machine Learning Model in the Cloud

This course will teach you how to complete a Data Science project from start to finish. As a result of this course, you'll deploy your 1st Machine Learning model in the Cloud. 

You'll learn how to develop a Machine Learning model that predicts "How would an article perform on a Data Science blog" based on the article's title.

Your model will be accessible with a link, which you can share with your future employers.

Are you thinking about pursuing a career in Data Science and don't have any experience yet?

I increasingly notice that there is a gap in understanding what do Data Scientists do. Many aspiring Data Scientists are then disappointed when expectations don't meet reality.  

This is also the main reason why I created this course. By completing this course you'll learn how Data Science looks in the real world.

Course Sample

Here's a sample from the course. No email address necessary

What do you get:

- A 60 pages Ebook in PDF, AW3 and EPUB format

- 10 Jupyter Notebooks with the code

What is this course about?

In this course you will learn how to train a Machine Learning model that predicts "How would an article perform on a Data Science blog" based on its title. 

What will you learn:

How to collect and analyze the data with Python and pandas

How to train the Machine Learning model with sklearn

What is Regularization

What is Bag of Words approach

What is Term Frequency–Inverse Document Frequency

What is the ROC curve

How to train a Machine Learning model

How to explain predictions of a Machine Learning model

How to start a server in AWS - inexpensive cloud computing services

How to build and deploy a Web Application

How to deploy a Machine Learning model in the Cloud

Chapters:

1. Introduction

2. Data Collection with Scrapping

3. Data Validation

4. Data Transformation

5. Exploratory Data Analysis

6. Feature Extraction

7. Modeling

8. Server

9. Deploying the Machine Learning model to AWS

10. Conclusion

About me

I’m a Senior Data Scientist with notable successes in improving systems for document classification, item recommendation and risk modeling. I obtained a Master's Degree in Computer Science in 2013. I have experience with managing teams, mentoring beginners and explaining complex concepts to non-engineers. 

I regularly tweet and blog about Data Science and Machine Learning.

FAQ

What are the prerequisites for the Course?

Basic knowledge of programming in Python and Jupyter Notebooks.

What's the refund policy?

If what you see is not what you expected, just reply to the download email within 10 days, and you'll get a full refund. No questions asked.

I have another question...

Please email me and I'd be happy to answer your question: orac.roman@gmail.com