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Numpy Basics For Machine Learning

Learn the basics of scientific computing package used by many Data Scientists.
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Content

Platform: Udemy
Video: 1h 33m
Language: English
Next start: On Demand

Table of contents

Description

If you are looking to become a data scientist, it is essential to learn linear algebra and what better way to learn it than by using Numpy as Python package that is so powerful that it was used to build sklearn(most popular machine learning package). Kick -start your data science career with the essentials of Numpy for strong foundation for understanding machine learning algorithms from a coding perspective. We will cover basics of Numpy like arrays, vectors, matrix operations and also have a use case in calculating Euclidean distance.

You will learn

✓ Basics of Numpy and linear algebra
✓ Python for data science
✓ Better prepared for learning machine learning
✓ Practice on Jupyter notebook or Google colab

Requirements

• Some programming experience
• A zeal to learn

This course is for

• Beginner Data Science
• Python programmers
• Any programmers interested in machine learning
Data Scientist
Expert analytics professional with 5 years experience in teaching and 4+ years experience as a data analytics professional. Currently working as a Data Scientist at a Canadian Financial Institute. I have worked extensively with software tools like SAS, R, and Python. In machine learning, my favorite topic is supervised learning – classification problems. Some of the machine learning algorithms I have used are logistic regression, decision trees, and neural networks.
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Platform: Udemy
Video: 1h 33m
Language: English
Next start: On Demand

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