Time

10 hours

Difficulty

Intermediate

In this guided lab brought to you by Next.Tech, you will learn the basics of machine learning in data science by learning the key mathematics utilized in common machine learning algorithims. As this course is focused on Machine Learning in Python, you will need a basic understanding of Python Programming and basic linear algebra.

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The Basics of Machine Learning

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Unlock modern machine learning techniques with Python by using the latest cutting-edge open source Python libraries.

This is Part 1 of the Python Machine Learning series. In this course, we provide a practical approach to key frameworks in data science and machine learning. We cover the mathematics behind several machine learning algorithms. Then, using we use Python to implement these algorithms from scratch and with the scikit-learn library.

Objectives

Understand the key frameworks in data science, machine learning, and deep learning, Harness the power of scikit-learn, Learn the mechanics of classification algorithms to implement the best tool for the job

Prerequisites

Basic Python programming and familiarity with the NumPy library, Understanding of basic linear algebra concepts, Knowledge of introductory calculus (preferable, but not necessary)