Real-World Machine Learning Projects with Scikit-Learn
- 4.2
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Brief Introduction
Predict heart disease, customer-buying behaviors, and much more in this course filled with real-world projectsDescription
Scikit-Learn is one of the most powerful Python Libraries with has a clean API, and is robust, fast and easy to use. It solves real-world problems in the areas of health, population analysis, and figuring out buying behavior, and more.
In this course you will build powerful projects using Scikit-Learn. Using algorithms, you will learn to read trends in the market to address market demand. You'll delve more deeply to decode buying behavior using Classification algorithms; cluster the population of a place to gain insights into using K-Means Clustering; and create a model using Support Vector Machine classifiers to predict heart disease.
By the end of the course you will be adept at working on professional projects using Scikit-Learn and Machine Learning algorithms.
About the Author
Nikola Živković is a software developer with over 7 years' experience in the industry. He earned a Master's degree in Computer Science from the University of Novi Sad back in 2011, but by then he was already working for several companies. At the moment he is a part of the Vega IT Sourcing team from Novi Sad. During his time in the industry, he worked on large enterprise systems, small web projects, data- and time-sensitive projects, as well as on machine learning projects. Apart from that, he has experience in knowledge sharing, talking at meetups, conferences, and as a guest lecturer at the University of Novi Sad. He is a video course author too, and he already has two courses published by Packt Publishing.
Requirements
- Requirements
- Familiarity with Scikit-Learn and Machine Learning algorithms will be helpful but not necessary since every algorithm will be explained in detail
Packt Publishing
4.2 Raiting
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