As the use of machine learning algorithms becomes popular for solving problems in a number of industries, so does the development of new tools for optimizing the process of programming such algorithms. This course aims to explain the scikit-learn API, which is a package created to facilitate the process of building machine learning applications. By explaining the difference between supervised and unsupervised models, as well as by applying algorithms to real-life datasets, this course will help beginners to start programming machine learning algorithms.
Two days
This course is perfect for beginners in the field of machine learning. No prior knowledge of the use of scikit-learn or machine learning algorithms is required. The students must have prior knowledge and experience of Python programming.
Before you start this course, you'll need to install Python 3.6, pip, scikit-learn, and the other libraries used in this course. You will find the steps to install these here:
You might need to use the python3 get-pip.py command, due to previous versions of Python on your computer are already using use the python command.
Using the pip command, install the following libraries:
Lesson 1: Introduction to scikit-learn
Lesson 2: Unsupervised Learning: Real-life Applications
Lesson 3: Supervised Learning: Key Steps
Lesson 4: Supervised Learning Algorithms: Predict Annual Income
Lesson 5: Artificial Neural Networks: Predict Annual Income
Lesson 6: Building your own Program
SKU | 035438SC |
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Weight | 1.1630 |
Coming Soon | No |
Days of Training | 2.0 |
Audience | Student |
Product Family | Partnerware |
Product Type | Print and Digital Courseware |
Electronic | Yes |
ISBN | No |
Language | English |
Page Count | 208 |
Curriculum Library | No |
Year | No |
Manufacturer's Product Code | No |
Current Revision | 1.0 |
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Revision Notes | No Revision Information Available |
Original Publication Date | 2019-01-16 00:00:00 |