Haskell: Data Analysis Made Easy
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Haskell: Data Analysis Made Easy

Master the art of data analysis by unleashing the power of Haskell
3.4 (5 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
70 students enrolled
Created by Packt Publishing
Last updated 4/2017
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Current price: $10 Original price: $200 Discount: 95% off
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  • 6.5 hours on-demand video
  • 8 Articles
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Understand the basic concepts of data analysis
  • Create Haskell functions for the common descriptive statistics functions
  • Learn to apply regular expressions in large-scale datasets
  • Plot data with the gnuplot tool and the EasyPlot library
  • Reduce the size of data without affecting the data’s effectiveness using Principal Component Analysis
  • Master the techniques necessary to perform multivariate regression using Haskell code
View Curriculum
  • A computer with internet connection
  • Enthusiasm to learn

A staggering amount of data is created everyday; analyzing and organizing this enormous amount of data can be quite a complex task. Haskell is a powerful and well-designed functional programming language that is designed to work with complex data. It is trending in the field of data science as it provides a powerful platform for robust data science practices.

This course will introduce the basic concepts of Haskell and move on to discuss how Haskell can be used to solve the issues by using the real-world data.

The course will guide you through the installation procedure, after you have all the tools that you require in place, you will explore the basic concepts of Haskell including the functions, and the data structures.

It will also discuss the various formats of raw data and the procedures for cleaning the data and plotting them.

With a good hold on the basics of Haskell and data analysis, you will then be introduced to advanced concepts of data analysis such as Kernel Density Estimation, Hypothesis Testing, Regression Analysis, Text Analysis, Clustering, Naïve Bayes Classification, and Principal Component Analysis.

Why go for this course?

We've spent the last decade working to help developers stay relevant. The structure of this course is a result of deep and intensive research into what real-world developers need to know in order to be job-ready. We don't spend too long on theory, and focus on practical results so that you can see for yourself how things work in action.

This course follows an example-based approach that will take you through learning Haskell initially, and then learning to manipulate data and visualizing it, and then gradually building your skill level where you can perform advanced algorithms on the data, such that you can make more sense of the data and interpret the future, or give suggestions. It's a blend of text, videos, code examples, and assessments, which together makes your learning journey all the more exciting and truly rewarding. It includes sections that form a sequential flow of concepts covering a focused learning path presented in a modular manner. This helps you learn a range of topics at your own speed and also move towards your goal of learning Haskell.

After completing this course, you will be equipped to analyze data and organize them using advanced algorithms.

This course is authored by some of the best in the field. 

We have combined the following best Haskell products by Packt:

  • Learning Haskell Programming by Hakim Cassimally
  • Getting Started with Haskell Data Analysis by James Church
  • Learning Haskell Data Analysis by James Church
  • Advanced Data Analysis with Haskell by James Church

Meet your expert instructions: 

James Church is an assistant professor of computer science at Austin Peay State University. He has consulted for various companies and a chemical laboratory for the purpose of performing data analysis work.

Hakim Cassimally learned the basics of Lisp 15 years ago and has been interested in functional programming ever since. He has written, spoken, and evangelised about learning and writing Haskell since 2006.

What are the requirements?

You do not need any programming knowledge, or knowledge in data science before you take up this course. 

What am I going to get from this course?

Learn the basics of Haskell

Learn how to clean data

Learn how to plot data on a graph and to draw conclusions based on the graphs

Apply advanced algorithms on the data to extract more information from the data.

Who is the target audience?
  • If you are new to the field of data analysis and wish to polish your data analysis skills by using Haskell, this course is all that you need.
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Curriculum For This Course
64 Lectures
How do I get Started with Haskell Data Analysis?
7 Lectures 23:27

Why Haskell

Installation Instructions for OS X

Installation Instructions for Windows

Installation Instructions for Linux

What Else Would You Need?
Getting Started with Haskell
6 Lectures 55:56

Built-in Data Structures

Editing Haskell Source Code

Introduction to Functions

Building Your Own Data Structures

Pattern Matching

Test you knowledge
2 questions
Working with CSV and SQLite3
6 Lectures 37:56

Data Range

Data Mean and Standard Deviation

Data Median

Data Mode

Converting CSV files to the SQLite3 format

Test your Knowledge
1 question
Cleaning Our Datasets
8 Lectures 35:10
Structured Versus Unstructured Datasets

Creating Your Own Structured Data

Counting the Number of Fields in Each Record

SQLite3 and Descriptive Statistics

Character Classes

Regular Expressions in CSV files

SQLite3 and Regular Expressions

Test your Knowledge
1 question
5 Lectures 32:19
Line Plots of a Single Variable

Plotting a Moving Average

Publication – Ready Plots

Feature Scaling

Scatter Plots

Test your Knowledge
1 question
Kernel Density Estimation
3 Lectures 25:00
What Is Normal Distribution?

Kernel Density Estimation

Application of the KDE

Test your Knowledge
2 questions
Hypothesis Testing
2 Lectures 22:25
Data in a Coin

Does a Home-Field Advantage Really Exist?
Regression Analysis
5 Lectures 48:10
Linear Regression

Correlation Coefficients

Drawbacks of Linear Regression

Logarithmic Regression

Polynomial Regression

Test your Knowledge
2 questions
Multiple Regression
4 Lectures 38:13
Building Matrices

Performing Multivariate Regression

Calculating the Adjusted R^2

Improving the Adjusted R^2 Score

Test your Knowledge
2 questions
Text Analysis
5 Lectures 28:15
Preparing Our Text

Finding the Set of N-Grams

Cosine Similarity

Overview of TF-IDF

Applying TF-IDF

Test your Knowledge
2 questions
4 More Sections
About the Instructor
Packt Publishing
3.9 Average rating
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51,940 Students
616 Courses
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Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.

With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now.

From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.

Packt Udemy courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.