Hello everyone! In just about two weeks, this summer's coding for Google Summer of Code will start. This year we have 8 projects, and I'm excited about each of them. I wanted to provide some details about each of these projects, to give an idea of what will be happening this summer. :)
------ "Revamp mlpack bindings", by Nippun Sharma mentored by Ryan Curtin, James Balamuta, and Yashwant Singh Now that mlpack not only provides a command-line interface but also an interface in Python, Julia, Go, and R, it has become a necessity to remove the single function interface that mlpack's bindings currently provide and use a more modern interface with which the user is more familiar. For Python, this means that each of mlpack's algorithms will be wrapped in a class that provides a scikit-like interface. Nippun is from Delhi, a big fan of music (he plays the drums) and likes driving. ------ "Improve tree ensemble support", by Rishabh Garg mentored by Ryan Curtin and German Lancioni Tree ensembles are arguably the best class of machine learning algorithms out there. They regularly win the competitive data science competitions. This project aims to implement the XGBoost algorithm to improve mlpack's tree ensemble support. Rishabh attends IIT Mandi, in India, and is very interested in both AI and cryptography. He also plays piano. ------ "Ready to Use Models in mlpack", by Aakash Kauhsik mentored by Kartik Dutt and Marcus Edel Aakash will implement MobileNetV1, which will also include implementing depthwise separable convolutions and a ResNet model builder that can be used to create ResNet18, ResNet34, ResNet50, ResNet101, and ResNet152. The ResNet builder and MobileNetV1 will fall into the models repository, and depthwise separable convolutions will fall into the mlpack repository as a layer inside the neural network codebase. Aakash is a student at the SRM Institute of Science and Technology in Chennai, India, and loves random conversations about all matter of things. ------ "Replacing boost::spirit", by Gopi Manohar Tatiraju mentored by Omar Shrit This project revolves around reducing the binary footprint of mlpack by replacing the functionality of boost::spirit to handle a more diverse range of data in mlpack. This project is a part of the bigger goal of removing boost dependencies. Gopi will reimplement mlpack's custom CSV parser that is currently being utilized to handle non-numeric data by adapting Armadillo's internal CSV parser to handle non-numeric data. Gopi studies at the Mukesh Patel School of Technology Management and Engineering in India, and has spent some time recently picking up finance and trading, including cryptocurrencies and NFTs. ------ "Example Zoo", by Roshan Swain mentored by Kartik Dutt and Marcus Edel Example Zoo is an implementation of mlpack showcasing its potential usage in the real-world domain. It will provide a better starting point for new users to learn from ready-to-run code. It will showcase the usage of the API, how it can be integrated with different visualization libraries for cool graphs and plots. Roshan is majoring in electrical engineering at the National Institute of Technology, Agartala, in India. He's planning to learn the violin when he's able. ------ "Example Zoo", by David Port Louis mentored by Kartik Dutt and Marcus Edel Example Zoo provides starters a gilmpse of most if not all features provided by mlpack, such that users can run the code for themselves to see it in action, maybe change things, break it, and figure out how to fix it. This would enable a starter to become familiar with the library relatively faster than reading documentation and starting from scratch. David is in Puducherry, India and likes gardening and cycling. ------ "Improvisation and Implementation of ANN Modules", by Abhinav Anand mentored by Marcus Edel Abhinav will be adding new layers (Upsample, Group Normalization, and ChannelShuffle) to the ANN module of mlpack. He will also improve the speed of pooling operations of max, mean, and LP pooling layers, and also will improve the speed of the un-pooling operation of mean pooling layers. Abhinav just graduated last month, and will soon start working. He is a chess expert and plays for at least half an hour every day. ------ "A Framework for Multiobjective Optimizers", by Nanubala Gnana Sai mentored by James Balamuta, Sayan Goswami, and Marcus Edel The ensmallen library boasts an extensive set of objective optimizers, almost all of which focus on single-objective problems. Previous works by Sayan Goswami paved the way for multiobjective optimizers. This was further complemented by the addition of Schaffer-N1 and Fonseca-Flemming test suites. This project will add optimizers, extend the test framework, and make ensmallen more accepting of multi-objective problems in general. Sai has been contributing to C++ machine learning projects for quite a while now, and previously was a part of the Shogun ML effort. He also likes to play piano, and is a fan of history. ------ If you want more information about each project, the Summer of Code website has more: https://summerofcode.withgoogle.com/projects/?sp-search=mlpack Anyway, these 8 great projects will get started soon! (Actually, some have already started. :)) All the students are available in the chat channels, so if you want to get to know them or have any questions about the projects, feel free to ask! Thanks, and have a great weekend! Ryan -- Ryan Curtin | "Chappie is in the car!" [email protected] | - Chappie _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
