In this post, I'll explore the new AWS Machine Learning services.

The problem we are trying to solve is to classify auto accident severity given a set of features. I'll not go into further details of the data set and what classification algorithms,etc. here since the goal of this blog is to explore the new AWS Machine Learning service step by step.

In the next blog post, I'll explore another service: Microsoft Azure Machine…

Added by Peter Chen on May 17, 2015 at 6:00pm — 3 Comments

As most of you guys know, the country of Nepal has been hit with a powerful earthquake killing over 1,800 lives(as of this writing). Thousands are injured. Lives are disrupted. Historic temples, monuments, buildings are leveled.

I plead you to help whatever you can. Money. Time. Good wishes, thoughts, and prayers. Scroll to the end of this post for where you…

Added by Peter Chen on April 25, 2015 at 10:00pm — 1 Comment

In this post, we’ll use an unsupervised machine learning technique called kmeans clustering to find naturual structures in our data. In the other blog posts, we used supervised machine learning techniques like logistic regression and linear regression to predict car prices or …

ContinueAdded by Peter Chen on April 4, 2015 at 6:00pm — No Comments

In this post, we’ll use a supervised machine learning technique called logistic regression to predict delayed flights. But before we proceed, I like to give condolences to the family of the the victims of the Germanwings tragedy.

This analysis is conducted using a public data set that can be obtained here:…

ContinueAdded by Peter Chen on March 29, 2015 at 6:00pm — 1 Comment

1. **Introduction:**

Let’s walk through an example of predictive analytics using a data set that most people can relate to:prices of cars. In this case, we have a data set with historical Toyota Corolla prices along with related car attributes.

Let’s load in the Toyota Corolla file and check…

Added by Peter Chen on March 22, 2015 at 11:00am — 8 Comments

This is part two of the series. In part one, we used linear regression model to predict the prices of used Toyota Corollas. There are some overlap in the materials for those just reading this post for the first time. For those who read the part 1 of the series using linear regression, then you can safely skip to the section where I applied neural networks to the same data set.

In this post, we will…

ContinueAdded by Peter Chen on March 22, 2015 at 10:30am — 1 Comment

- Experimenting with AWS Machine Learning for Classification
- Visualizing Nepal Earthquake: The Human Side of Data Science
- Finding Group Structures in Data using Unsupervised Machine Learning
- Predicting Flights Delay Using Supervised Learning, Logistic Regression
- Predicting Car Prices Part 1: Linear Regression
- Predicting Car Prices Part 2: Using Neural Network

- Predicting Car Prices Part 1: Linear Regression
- Predicting Flights Delay Using Supervised Learning, Logistic Regression
- Predicting Car Prices Part 2: Using Neural Network
- Experimenting with AWS Machine Learning for Classification
- Finding Group Structures in Data using Unsupervised Machine Learning
- Visualizing Nepal Earthquake: The Human Side of Data Science

- data (1)
- earthquake (1)
- nepal (1)
- relief (1)
- visualization (1)

© 2020 Data Science Central ® Powered by

Badges | Report an Issue | Privacy Policy | Terms of Service

**Most Popular Content on DSC**

To not miss this type of content in the future, subscribe to our newsletter.

- Book: Statistics -- New Foundations, Toolbox, and Machine Learning Recipes
- Book: Classification and Regression In a Weekend - With Python
- Book: Applied Stochastic Processes
- Long-range Correlations in Time Series: Modeling, Testing, Case Study
- How to Automatically Determine the Number of Clusters in your Data
- New Machine Learning Cheat Sheet | Old one
- Confidence Intervals Without Pain - With Resampling
- Advanced Machine Learning with Basic Excel
- New Perspectives on Statistical Distributions and Deep Learning
- Fascinating New Results in the Theory of Randomness
- Fast Combinatorial Feature Selection

**Other popular resources**

- Comprehensive Repository of Data Science and ML Resources
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- 100 Data Science Interview Questions and Answers
- Cheat Sheets | Curated Articles | Search | Jobs | Courses
- Post a Blog | Forum Questions | Books | Salaries | News

**Archives:** 2008-2014 |
2015-2016 |
2017-2019 |
Book 1 |
Book 2 |
More

**Most popular articles**

- Free Book and Resources for DSC Members
- New Perspectives on Statistical Distributions and Deep Learning
- Time series, Growth Modeling and Data Science Wizardy
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- How to Automatically Determine the Number of Clusters in your Data
- Fascinating New Results in the Theory of Randomness
- Hire a Data Scientist | Search DSC | Find a Job
- Post a Blog | Forum Questions