This course introduces machine learning covering the three main techniques used in industry: regression, classification, and clustering.
It is designed to be self-contained, easy to approach, and fast to assimilate.
You will learn:
What machine learning is
Where machine learning is used in industry
How to recognize the technique you should use
How to solve regression problems to predict numerical quantities
How to solve classification problems to predict categorical quantities
How to use clustering to group your data and discover new insights
The course is designed to maximize the learning experience for everyone and includes 50% theory and 50% hands-on practice. It includes labs with hands-on exercises and solutions.
No software installation required. You can run the code on Google CoLab and get started right away.
This course is the fastest way to get up to speed in machine learning and Scikit Learn.
Why Machine Learning?
Machine Learning has taken the world by a storm in the last 10 years, revolutionizing every company and empowering many applications we use every day.
Here are some examples of where you can find machine learning today: recommender systems, image recognition, sentiment analysis, price prediction, machine translation, and many more!
There are over 3000 job announcements requiring Scikit Learn in the United States alone, and almost 80000 jobs mentioning machine learning in the US. Machine Learning engineers can easily earn six figure salaries in major cities, and companies are investing Billions of dollars in developing their teams.
Even if you already have a job, understanding how machine learning works will empower you to start new projects and get visibility in your company.
Why Scikit Learn?
It's the best Python library to learn machine learning
Simple, yet powerful API for predictive data analysis
Used in many industries: tech, biology, finance, insurance
Built on standard libraries such as NumPy, SciPy, and Matplotlib
