Introduction to Machine Learning Course

Introduction to Machine Learning Course
at
UDACITY
Overview

Skills you will learn

What are the course deliverables?

Machine Learning is a first-class ticket to the most exciting careers in data analysis today. As data sources proliferate along with the computing power to process them, going straight to the data is one of the most straightforward ways to quickly gain insights and make predictions.
Machine learning brings together computer science and statistics to harness that predictive power. It’s a must-have skill for all aspiring data analysts and data scientists, or anyone else who wants to wrestle all that raw data into refined trends and predictions.
This is a class that will teach you the end-to-end process of investigating data through a machine learning lens. It will teach you how to extract and identify useful features that best represent your data, a few of the most important machine learning algorithms, and how to evaluate the performance of your machine learning algorithms.
This course is also a part of our
Data Analyst
Nanodegree.

More about this course

This is a class that will teach you the end-to-end process of investigating data through a machine learning lens
It will teach you how to extract and identify useful features that best represent your data, a few of the most important machine learning algorithms, and how to evaluate the performance of your machine learning algorithms

Welcome to Machine Learning

Naive Bayes

Support Vector Machines

Decision Trees

Choose your own Algorithm

Datasets and Questions

Regressions

Outliers

Clustering

Feature Scaling

Katie Malone

Designation : Instructor

Sebastian Thrun

Designation : Instructor

Eligibility criteria Up Arrow Icon

To succeed in this course, you must be proficient at programming in Python and basic statistics. If you need a refresher on any of these topics, you can check out these courses: Intro to Python Programming Inferential Statistics Descriptive Statistics One additional course that would be nice to have is Intro to Data Science , as this will get you familiar with scientific problem-solving. However, completion of that class isn't required for success. We will also use a tiny bit of git , which you can also learn about on Udacity. One thing that we don’t require is previous exposure to machine learning. If you’re a machine learning beginner, you’re in the right place.

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