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The Machine Learning and Artificial Intelligence Challenge

This competition has ended

Artificial Intelligence is transforming everyday life. It changes how you interact with your phone, your computer, your car, even your friends online. It can protect you from fraud or choose your next movie to watch. It can show you patterns you didn’t even know existed and transform gut instincts into consistent rules. It’s something you need to understand, and it can be a lot of fun.

We want you to take three simple scenarios and use the Artificial Intelligence and Machine Learning tools and techniques available to come up with some simple, innovative, maybe even surprising solutions to some familiar problems.

Don’t be scared! These problems may seem big, but there are surprisingly simple solutions and plenty of examples online that will get you there quickly.

Points are given for speed, accuracy and the use of technology. Use Azure AI, use Redis, or Python. Write it in Javscript to run in a browser. Whatever works for you. Be adventurous and spread your wings. 

Spam

The classic spam filter.

We’ll provide you with three sets of data: one contains spam, one contains ham (ham is not spam. Or the other way around?) and the third contains random test data. You build and train your system using the first two sets and then run it against the third set. Fight the spam and Save the World.

Your training and test data are here. The format is simple: A text file with 1 message per line, each line begins with "Spam" or "Ham" (ham is "not spam"), followed by a comma and then the message. The file is in 3 parts, each part labelled by a header starting with #. There's spam and ham messages for training, followed by a set of messages that are to be used for testing your code.

Train your model on the training data, then test on the test data. We may then send you some unlabelled test data so beware! Write up your methodology and code in a short article and report your results.

Your article should be posted in the Artificial Intelligence and Machine Learning section.

Difficulty: Beginner to Intermediate

detective

The language detector

We all love code but we all really love code that’s colourised. The only problem is your colouriser needs to know the language of the code before it can run.  We’ll provide you with a collection of labelled code snippets. The code snippets could be big or small, clear or ambiguous.

Your training and test data are here. The format is simple: A text file containing HTML, with the HTML comprising PRE blocks that contain a code sample. The language of the same is given by the lang attribute of the PRE tag. Train and test your model on the data provided then write up your methodology and code in a short article and report your results.

The goal is to make the code look good so as a hint you may not need to be 100% accurate. If it looks like JavaScript and smells like JavaScript then sometimes C++ will be OK. How picky you are is up to you.

Your article should be posted in the Artificial Intelligence and Machine Learning section.

Difficulty: Intermediate

feather

Birds of a Feather stick together.

If you’re into a particular technology you’re likely to read, vote or download content surrounding that technology. By looking at patterns of behviour you can make an educated guess about what one person may like based on how similar or disimilar their actions are to others.

We’ve generated some user data that revolves around a set of articles. Each article has one or more tags, and over the course of 30 days users are reading, upvoting or downvoting articles as well as downloading files assoicated with the articles.

Your job is to decide how important each action is. Is an upvote more significant than a file download? Is a downvote important? What about the tags associated with each article? The viewing habits? How does it all fit together?

Build a model that can input this data and make a decision on whether a given user would .be interested in a given article, and that, given a user, can suggest articles most likely to be of interest.

Difficulty: Intermediate to Advanced

Resources

There are hundreds of easy to read articles that provide basic examples of machine learning that you can adapt to these problems. Here are just a few:

Current Entries

Articles that match the contest criteria are automatically entered.

3 Mar 2018
sjb_strat
Create a Spam Filter Using Machine Learning
3 Mar 2018
Omar Gameel Salem
Using Collaborative Filtering to find people who share tastes, and for making automatic recommendations based on things that other people like.
3 Mar 2018
sjb_strat
Use machine learning to determine the programming language of text
6 Mar 2018
Arthur V. Ratz
In this article we'll discuss on how to produce user-to-item recommendations by using SVD++, Pearson Correlation and probability-based similarity computation
12 Mar 2018
Peter Leow
Design and implement a simple AI agent that can learn and fight the relentless spam plague.
3 Mar 2018
Thomas Daniels
This article describes how to use a neural network to recognize programming languages, as an entry for CodeProject's Machine Learning and Artificial Intelligence Challenge.
11 Mar 2018
Arthur V. Ratz
In this article we’ll formulate and thoroughly discuss about probabilistic Bayesian classification algorithm and its implementation in Node.JS and JavaScript that can be actively used to detect and locate messages containing potential spam and other unsolicited data.
1 Mar 2018
Philipp_Engelmann
With recent scientific advancements in Deep Learning, Artificial Intelligence and Neural Networks, as well as steadily evolving tools such as Tensorflow, Pytorch, and Keras, writing, testing and optimizing your own Neural Networks is now easier than ever before.
20 Feb 2018
Byte-Master-101
Now that we got the basics over with, It's time for improvement!
6 Feb 2018
raddevus
Entry in the Artificial Intelligence and Machine Learning Contest. Here's how I learned / guessed how to find spam.
5 Mar 2018
Kornfeld Eliyahu Peter
The Machine Learning and Artificial Intelligence Challenge
12 Feb 2018
Scott Clayton
Train a binary classifier in Azure and then use it in a C# application.
26 Feb 2018
Markus Glagla
I will show how to prepare training and test data, define a simple neural network model, train and test it.
26 Feb 2018
Nikola M. Živković
Have you ever wondered how Facebook knows how to suggest the right friend to tag? Speaking of it, how does the Google’s image search algorithm work? Yes, you are right, there is a neural network involved in all those tasks.
1 Mar 2018
Scott Clayton
Detect the programming language of a code snippet using neural networks in Azure ML Studio
3 Mar 2018
Vince Chan
A walkthrough of common machine learning tasks - by building a Naive Bayes Spam Classifier using python and scikit-learn
11 Feb 2018
Nikola M. Živković
Introduction to TensorFlow with Python example
12 Feb 2018
Shun Huang
In the previous article, Machine Learning Basics and Perceptron Learning Algorithm, the assumption was that the Iris Data Set trained by Perceptron Learning Algorithm is linear separable, so the number of misclassification on each training iteration eventually converge to 0.
12 Feb 2018
Nikola M. Živković
Back in 2015. Google released TensorFlow, the library that will change the field of Neural Networks and eventually make them mainstream. Not only that it became popular for developing Neural Networks, but it enabled higher-level APIs to run on top of it. One of those APIs is Keras.

Current Participants

Those with articles that match the contest criteria are automatically entered.

Arthur V. Ratz
Software Developer (Senior) EpsilonDev
Ukraine Ukraine
I’m software developer, system analyst and network engineer, with over 20 years experience, graduated from L’viv State Polytechnic University and earned my computer science and information technology master’s degree in January 2004. My professional career began as a financial and accounting software developer in EpsilonDev company, located at L’viv, Ukraine. My favorite programming languages - C/C++, C#.NET, Java, ASP.NET, Node.js/JavaScript, PHP, Perl, Python, SQL, HTML5, etc. While developing applications, I basically use various of IDE’s and development tools, including Microsoft Visual Studio/Code, Eclipse IDE for Linux, IntelliJ/IDEA for writing code in Java. My professional interests basically include data processing and analysis algorithms, artificial intelligence and data mining, system analysis, modern high-performance computing (HPC), development of client-server web-applications using various of libraries, frameworks and tools. I’m also interested in cloud-computing, system security audit, IoT, networking architecture design, hardware engineering, technical writing, etc. Besides of software development, I also admire to write and compose technical articles, walkthroughs and reviews about the new IT- technological trends and industrial content. I published my first article at CodeProject in June 2015.
Byte-Master-101
Student
Egypt Egypt
Hello, I'm a programmer by day, and a Jedi Ninja by night! I mean... I like programming Neural Networks. I'm kinda experienced with C#, JavaScript, MySQL, Network Programming, Unity Game Programming and a bit of C++. I also tried out freelancing for a few months, and it worked well. If anybody wants to talk to me, you can contact me on email(mokhtar.mohammed.red@gmail.com) or on Skype(mokhtar.mohammed.red@gmail.com).
Kornfeld Eliyahu Peter
Software Developer (Senior)
Israel Israel
Born in Hungary, got my first computer at age 12 (C64 with tape and joystick). Also got a book with it about 6502 assembly, that on its back has a motto, said 'Try yourself!'. I believe this is my beginning...

Started to learn - formally - in connection to mathematics an physics, by writing basic and assembly programs demoing theorems and experiments.

After moving to Israel learned two years in college and got a software engineering degree, I still have somewhere...

Since 1997 I do development for living. I used 286 assembly, COBOL, C/C++, Magic, Pascal, Visual Basic, C#, JavaScript, HTML, CSS, PHP, ASP, ASP.NET, C# and some more buzzes.

Since 2005 I have to find spare time after kids go bed, which means can't sleep to much, but much happier this way...

Free tools I've created for you...


Markus Glagla
Web Developer
Germany Germany
No Biography provided
Nikola M. Živković
Software Developer (Senior) Vega IT Sourcing
Serbia Serbia
Read more at my blog: https://rubikscode.net
Omar Gameel Salem
Software Developer
Egypt Egypt
Enthusiastic programmer/researcher, passionate to learn new technologies, interested in problem solving, data structures, algorithms, AI, machine learning and nlp.

Amateur guitarist/ keyboardist, squash player.
Peter Leow
Instructor / Trainer
Singapore Singapore
Stop by my website at https://peterleowblog.com/

Check out my publications at https://www.amazon.com/author/peterleow

Follow me on twitter at https://twitter.com/peterleowblog

“Live as if you were to die tomorrow. Learn as if you were to live forever.”
― Mahatma Gandhi

子曰:"三人行,必有我师焉;择其善者而从之,其不善者而改之."
Philipp_Engelmann
Software Developer (Senior)
Germany Germany
Hi there 🙂
My name is Philipp Engelmann, I work as a web developer at FIO SYSTEMS AG in Leipzig. I am interested in C#, Python, (REST-)API-Design, software architecture, algorithms and AI. Check out my blog at https://cheesyprogrammer.com/
raddevus
Software Developer (Senior) RADDev Publishing
United States United States
Roger has worked in IT for over 25 years in numerous roles (Technical Support, Quality Assurance, Capacity & Performance Engineering and Software Development).
During that time, he has recognized that software often just becomes another layer of work that the user has to wade through.
Sometimes technical documentation is like that too: so confusing and complex that it wastes developers' time.
That's why when he writes his books like Programming Windows 10 Via UWP and his articles (Practical Electronics For Makers) he strives to explain things in the shortest available space with the simplest language possible. Often that means, writing in a tutorial style with numerous images to help guide the user.
He believes the best guiding principle is Einstein's famous quote: "Everything should be made as simple as possible, but not simpler."
Rupesh Sreeraman
Technical Lead ARS Traffic and Transport Technology
India India
Creator of NeuralStyler AI,CodAI,ExMplayer
Scott Clayton
Software Developer
United States United States
Scott enjoys working on proof-of-concept projects for the sake of learning new and interesting ways to solve problems.
Shun Huang
Software Developer (Senior)
United States United States
My name is Shun. I am a software engineer and a Christian. I currently work at a startup company.
My blog: shunsvineyard.info
Email: sincerelygre@protonmail.com
sjb_strat
CognitiveCoder.com
United States United States
I am a software engineer with over 17 years of experience working mainly in backend development (.NET, NodeJS, and Python) but increasingly working on the front-end with Angular and React.

In the last 1.5 to 2 years my passion has turned to everything that has anything to do with machine learning, deep learning, and artificial intelligence. Not just the abstract, theoretical parts of it but actually building and delivering end-to-end ML, DL, and AI backed solutions into production.

If you are a software engineer who is starting to realize that in the very near future the term "full stack" is going to require the ability to understand, build, and deliver ML, DL, and AI backed solutions then visit my blog CognitiveCoder.com - it's built for people like us.
Thomas Daniels
Student
Belgium Belgium
Also known as ProgramFOX. I like programming, playing chess and astronomy. Administrator of Chess Variants Training[^].

Find me on:
Vince Chan
Software Developer (Senior)
United States United States
No Biography provided

These rules (and the CodeProject® Terms of Use and the CodeProject Contributors Agreement) govern the Machine Learning and Artificial Intelligence Challenge (the "Contest") and set out the terms and conditions between CodeProject and its affiliates ("CodeProject" or "us/we") and each participant ("participant", "or "you"). A submission to this Contest constitutes your acceptance of these Official Contest Rules (the "Rules").

1. How to Enter: CodeProject is offering the Contest and will award Prizes (as defined below) based on the results of judging all valid entries against the criteria established in these Rules.

The Contest begins on  5 February 2018 at 12AM and ends on 4 March 2018 at 11:59:59 PM US Eastern Daylight Time (“Contest Period”). CodeProject’s clock is the official time for the Contest. All entries must be submitted during this period in order to qualify.

To enter the Contest, write an article or articles that address 1 or more of the challenges presented by the Contest.and submit it to the Artificial Intelligence and Machine Learning section of CodeProject.com before the end of the Contest Period. Participants must comply with the submission format provided by CodeProject on its website. Submissions must be in the English language.

No purchase is necessary to enter the Contest or to be eligible to win a Prize.

We are not responsible for lost, illegible, incomplete, mutilated or stolen entries; errors appearing within these Rules, in any Contest related advertisements or other materials; or other errors of any kind whether mechanical, human, electronic or otherwise. Entries that are late, illegible, incomplete, unreadable, damaged, delayed, lost, tampered with, incomprehensible, forged, mutilated, misdirected, inaccurate, unintelligible or otherwise not in compliance with these Rules will be disqualified. You must provide all of the requested information to submit a valid entry. Only those who live in jurisdictions in which this Contest is legal may enter.

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Prizes may not be exactly as shown. A reasonable US$ equivalent in lieu of the Prize may also be awarded at the sole discretion of CodeProject.

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Eligible entries will be judged by CodeProject judges at the end of the contest period. Prizes will be awarded based on how closely an entry adheres to the conditions of entry, including but not limited to:

  • how clear, pertinent, simple and enjoyable the article is;
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  • how effectively the application demonstrates creativity, understanding of the concepts and available tools and services; and
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Announcements

 
NewsTest data has been updated Pin
Chris Maunder13-Feb-18 15:23
adminChris Maunder13-Feb-18 15:23 

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Discussions

 
GeneralNow Microsoft Azure published resources submitted as a part of my two articles are back to work and became fully operational over again . Pin
Arthur V. Ratz10-Mar-18 23:55
mvaArthur V. Ratz10-Mar-18 23:55 
Generalhttps://user2item.azurewebsites.net/ and http://antispaminfo.eastus2.cloudapp.azure.com/ are now available... Pin
Arthur V. Ratz7-Mar-18 2:57
mvaArthur V. Ratz7-Mar-18 2:57 
GeneralRe: https://user2item.azurewebsites.net/ and http://antispaminfo.eastus2.cloudapp.azure.com/ are now available... Pin
Chris Maunder9-Mar-18 14:14
adminChris Maunder9-Mar-18 14:14 
GeneralRe: https://user2item.azurewebsites.net/ and http://antispaminfo.eastus2.cloudapp.azure.com/ are now available... Pin
Arthur V. Ratz9-Mar-18 17:53
mvaArthur V. Ratz9-Mar-18 17:53 
GeneralRe: https://user2item.azurewebsites.net/ and http://antispaminfo.eastus2.cloudapp.azure.com/ are now available... Pin
Arthur V. Ratz10-Mar-18 23:52
mvaArthur V. Ratz10-Mar-18 23:52 
Generalhttp://antispaminfo.eastus2.cloudapp.azure.com/ is now back to work from maintainance Pin
Arthur V. Ratz25-Feb-18 5:16
mvaArthur V. Ratz25-Feb-18 5:16 
GeneralUser Behavior Data Pin
Scott Clayton24-Feb-18 9:03
memberScott Clayton24-Feb-18 9:03 
GeneralRe: User Behavior Data Pin
Chris Maunder4-Mar-18 2:26
adminChris Maunder4-Mar-18 2:26 
GeneralRe: User Behavior Data Pin
Scott Clayton4-Mar-18 7:46
memberScott Clayton4-Mar-18 7:46 
GeneralThe final revision of Naїve Bayesian Anti-Spam Filter Web Application has been finally deployed on Microsoft Azure... Pin
Arthur V. Ratz24-Feb-18 0:38
mvaArthur V. Ratz24-Feb-18 0:38 
QuestionBirds of a feather - test data? Pin
Omar Gameel Salem21-Feb-18 18:36
professionalOmar Gameel Salem21-Feb-18 18:36 
GeneralConflict of interest Pin
Uzi Granot17-Feb-18 2:32
memberUzi Granot17-Feb-18 2:32 
GeneralRe: Conflict of interest Pin
Chris Maunder18-Feb-18 16:57
adminChris Maunder18-Feb-18 16:57 
GeneralLanguageTraining.txt Pin
Scott Clayton12-Feb-18 13:38
memberScott Clayton12-Feb-18 13:38 
GeneralRe: LanguageTraining.txt Pin
Chris Maunder13-Feb-18 12:12
adminChris Maunder13-Feb-18 12:12 
GeneralRe: LanguageTraining.txt Pin
Scott Clayton14-Feb-18 13:02
memberScott Clayton14-Feb-18 13:02 
GeneralBirds of a Feather: user actions -> simultaneous up and down votes Pin
jamessdixon9-Feb-18 10:02
memberjamessdixon9-Feb-18 10:02 
GeneralRe: Birds of a Feather: user actions -> simultaneous up and down votes Pin
Chris Maunder12-Feb-18 9:33
adminChris Maunder12-Feb-18 9:33 
GeneralBirds of a Feather: articles - duplicate tags Pin
jamessdixon9-Feb-18 7:22
memberjamessdixon9-Feb-18 7:22 
GeneralRe: Birds of a Feather: articles - duplicate tags Pin
Chris Maunder12-Feb-18 9:34
adminChris Maunder12-Feb-18 9:34 
GeneralLanguage training data is corrupted Pin
Tomaž Štih8-Feb-18 2:33
memberTomaž Štih8-Feb-18 2:33 
GeneralRe: Language training data is corrupted Pin
Chris Maunder8-Feb-18 4:14
adminChris Maunder8-Feb-18 4:14 
GeneralQuestion Pin
Jon McKee5-Feb-18 18:43
professionalJon McKee5-Feb-18 18:43 
GeneralRe: Question Pin
Chris Maunder7-Feb-18 9:04
adminChris Maunder7-Feb-18 9:04 
GeneralRe: Question Pin
Jon McKee7-Feb-18 11:41
professionalJon McKee7-Feb-18 11:41 

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5 Feb - 5 Mar 2018

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