Book Image

Data Science Algorithms in a Week

By : Dávid Natingga
Book Image

Data Science Algorithms in a Week

By: Dávid Natingga

Overview of this book

<p>Machine learning applications are highly automated and self-modifying, and they continue to improve over time with minimal human intervention as they learn with more data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed that solve these problems perfectly. Data science helps you gain new knowledge from existing data through algorithmic and statistical analysis.</p> <p>This book will address the problems related to accurate and efficient data classification and prediction. Over the course of 7 days, you will be introduced to seven algorithms, along with exercises that will help you learn different aspects of machine learning. You will see how to pre-cluster your data to optimize and classify it for large datasets. You will then find out how to predict data based on the existing trends in your datasets.</p> <p>This book covers algorithms such as: k-Nearest Neighbors, Naive Bayes, Decision Trees, Random Forest, k-Means, Regression, and Time-series. On completion of the book, you will understand which machine learning algorithm to pick for clustering, classification, or regression and which is best suited for your problem.</p>
Table of Contents (12 chapters)
11
Glossary of Algorithms and Methods in Data Science

Problems

  1. Cloud storage prediction cost: Our software application generates data on a monthly basis and stores this data in cloud storage together with the data from the previous months. We are given the following bills for the cloud storage and we would like to estimate the running costs for the first year of using this cloud storage:

Month of using the cloud storage

Monthly bill in euros

1

120.0

2

131.2

3

142.1

4

152.9

5

164.3

1 to 12

?

  1. Fahrenheit and Celsius conversion: In the earlier example, we devised a formula converting degrees Fahrenheit into degrees Celsius. Devise a formula converting degrees Celsius into degrees Fahrenheit.
  2. Flight time duration prediction from the distance: Why do you think that a linear regression model resulted in the estimation of the speed to be 1192 km/h as opposed to the real speed of about 850...