Machine Learning Practical: 6 Real-World Applications

Machine Learning – Get Your Hands Dirty by Solving Real Industry Challenges with Python

What you’ll learn

  • You will know how a real data science project looks like
  • You will be able to include these Case Studies in your resume
  • You will be able better market yourself as a Machine Learning Practitioner
  • You will feel confident during the Data Science interview
  • You will learn how to chain multiple ML algorithms together to achieve the goal
  • You will learn the most advanced Data Visualization techniques with Seaborn and Matplotlib
  • You will learn Logistic Regression
  • You will learn L1 Regularization (Lasso)
  • You will learn Random Forest Classifier


  • You need to know Python (Machine Learning A-Z level is enough) in order to complete this Machine Learning Practical: 6 Real-World Applications course.
  • You need to know how to set up your working environment (Anaconda, Jupyter Notebook, Spyder)
  • This should not be your first Machine Learning course. You need to understand the main concepts.


You understand the theory of Machine Learning and understand how to create your very first algorithms. Now what?

There are lots of the Machine Learning Practical: 6 Real-World Applications courses out there about the underlying theory of Machine Learning which do not go any much deeper– into the applications.

Trending Now:   Python : Machine Learning, Deep Learning, Pandas, Matplotlib

This course is not one of them.

Are you prepared to use all of the theory and understanding to reality Machine Learning difficulties?

Welcome to “Machine Learning Practical”.

We compiled the finest industry specialists with lots of finished projects behind.

Each presenter has a distinct style, which is identified by his experience, and like in a real life, you will require adapt to it if you desire effectively total this course. We will leave nobody behind!

This Machine Learning Practical: 6 Real-World Applications course will debunk how a real Data Science project appears like. Time to move far from these refined examples which are just presenting you to the matter, however not offering any real experience.

If you are still dreaming about where to find out Machine Learning through practice, where to take real-life projects for your CV, how to not look like a noob in the employer’s eyes, then you concerned about the best location!

This Machine Learning Practical: 6 Real-World Applications course supplies a hands-on technique to real-life obstacles and covers precisely what you require to prosper in the real life of Data Science.

There are most amazing case studies consisting of:

  • ● detecting diabetes in the early stages
  • ● directing customers to membership items with app use analysis
  • ● reducing churn rate in financing
  • ● anticipating customer area with GPS data
  • ● forecasting future currency exchange rates
  • ● categorizing fashion
  • ● anticipating breast cancer
  • ● and a lot more!
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All real.

All real.

All practical and applicable.

And as a last reward:

In this Machine Learning Practical: 6 Real-World Applications course, we will likewise cover Deep Learning Techniques and their useful applications.

As you can see, our objective here is to truly build the World’s leading useful machine finding out course.

If your objective is to end up being a Machine Learning professional, you understand how important these real-life examples actually are.

They will identify the distinction in between Data Scientists who feel in one’s bones the theory and Machine Learning professionals who have actually gotten their hands dirty.

If you desire to get hands-on experience which you can include to your portfolio, then this Machine Learning Practical: 6 Real-World Applications course is for you.

Register now and we’ll see you within.

Who this course is for:

  • Data Science and Machine Learning lovers who wish to comprehend how real data science projects appear like.
  • Anybody with Machine Learning and Python understanding who wishes to practice their abilities

Created by Kirill Eremenko, Hadelin de Ponteves, Dr. Ryan Ahmed, Ph.D., MBA, SuperDataScience Team, Rony Sulca

Last updated **/2020
4.05 GB

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