![]() For up-to-date status of the challenge you can check the leaderboard: We have also the first participants started posting results and my benchmark result was broken in less than 12 hours. Kaggle community has been collaborating and solving some very hard problems – like Higgs Boson machine learning challenge – see the list of top challenges on front page.ĭuring the first 3 days of this Morse Learning Machine challenge there has been almost 100 downloads of the provided open source Morse decoder (Python based, there is also C++ code available for free), audio material and sample submission file. This is a great opportunity for people who are interested in gaining knowledge about software development, data science, statistical data analysis, machine learning algorithms etc. This second competition will distortions introduced by normal radio paths and hand-sent code, which can also be more difficult to answer. If this competition is successful, a more difficult competition will be set up. The competition ends on December 27, which seems kind of short to me, but this is only phase 1. There is also some new tools I posted to Github. You can of course leverage the experimental multichannel CW decoder I recently implemented on FLDIGI or the standalone version of Bayesian decoder written in C++. ![]() ![]() While this software is purely experimental version it has some features of the FLDIGI Morse decoder but implemented using Python instead of C++. I have also provided sample Python Morse decoder to make it easier too get started. A real-time leaderboard shows participants their current standing based on their validation set predictions. To evaluate their progress and compare themselves with others, they can submit their prediction results on-line to get immediate feedback. The data labels are provided for a training set so the participants can self-evaluate their systems. WAV audio files containing short sequences of randomized Morse code. To that end, they get development data consisting of 200. ![]() In addition to the prize money and data, they use Kaggle to meet, learn, network and collaborate with experts from related fields.ĭuring the competition, the participants build a learning system capable of decoding Morse code. They come from over 100 countries and 200 universities. According to the website, the Kaggle community includes tens of thousands of PhDs from quantitative fields such as computer science, statistics, econometrics, maths and physics, and industries such as insurance, finance, science, and technology. Kaggle is actually a very interesting website. The Kaggle Morse Challenge was approved a couple of days ago. AG1LE has set up a Kaggle competition whose goal is to build a machine that learns how to decode audio files containing Morse Code. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |