13 papers · ranked by Valyu relevance
Daniel Alabi, Joseph Ekpenyong, Alida Monaco
The NaijaCoder in-person summer camps are intensive programs for high school and pre-college students in Nigeria. The programs are meant to provide free instruction on the basics of algorithms and computer programming. In 2024, the camps were held in two locations within the country: (i) the Federal Capital Territory…
Pohsun Feng, Ziqian Bi, Yizhu Wen, Benji Peng + 11 more
Language Models -- AutoML from Basics to State-of-the-Art Techniques Authors: ['Pohsun Feng' 'Ziqian Bi' 'Yizhu Wen' 'Benji Peng' 'Junyu Liu' 'Caitlyn Heqi Yin' 'Tianyang Wang' 'Keyu Chen' 'Sen Zhang' 'Ming Li' 'Jiawei Xu' 'Ming Liu' 'Xiaoyong Pan' 'Jinlang Wang' 'Qian Niu'] | 1 | Introduction to AutoML | | 13 | | ---…
Ian Stewart, Katherine A. Keith
Many scientific fields—including biology, health, education, and the social sciences—use machine learning (ML) to help them analyze data at an unprecedented scale. However, ML researchers who develop advanced methods rarely provide detailed tutorials showing how to apply these methods. Existing tutorials are often…
Gustavo Schiavone Crestana, Ubiratan da Silva Batista, Michelli Inácio Gonçalves Funnicelli, Larissa Graciano Braga + 9 more
The rapid evolution of high-throughput technologies in biosciences has generated diverse and voluminous datasets, requiring bioscientists to develop data manipulation and analysis skills. Python, known for its versatility and powerful libraries, has become a crucial tool for managing these datasets. However, there is a…
Thomas Bartz–Beielstein
The goal of hyperparameter tuning (or hyperparameter optimization) is to optimize the hyperparameters to improve the performance of the machine or deep learning model. spotPython ("Sequential Parameter Optimization Toolbox in Python") is the Python version of the well-known hyperparameter tuner SPOT, which has been…
Anthony T. Bogetti, Jeremy M. G. Leung, John D. Russo, She Zhang + 11 more
We present six advanced tutorials instructing users in the best practices of using key new features and plugins/extensions of the WESTPA 2.0 software package, which consists of major upgrades for enabling applications of the weighted ensemble (WE) path sampling strategy to even larger systems and/or slower processes.…
Rohitash Chandra, Royce Chen, Joshua A. Simmons
Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain Monte-Carlo (MCMC) sampling methods are used to implement Bayesian inference. In the past three decades, MCMC sampling methods have…
Lucy Moctezuma, Lorena Benitez Rivera, Florentine van Nouhuijs, Faye Orcales + 4 more
This manuscript describes the development of a module that is part of a learning platform named “NIGMS Sandbox for Cloud-based Learning” https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers…
Ali Arya
| 3 | Table of Content | | --- | --- | | Preface 8 | | | Notes 10 | | | 10 | Code Examples | | Signage and Numbering 11 | | | 12 | Chapter 1: Introduction | | 12 | 1.1. At the Restaurant | | 15 | 1.2. Algorithms | | 1.3. Programs 17 | | | 1.4. Programming and Algorithmic Thinking 21 | | | 25 | 1.5. Modularization | |…
Pattara Leelaprute, Bodin Chinthanet, Supatsara Wattanakriengkrai, Raula Gaikovina Kula + 2 more
'Raula Gaikovina Kula' 'Pongchai Jaisri' 'Takashi Ishio'] In the field of data science, and for academics in general, the Python programming language is a popular choice, mainly because of its libraries for storing, manipulating, and gaining insight from data. Evidence includes the versatile set of machine learning…
Matteo De Matola, Giorgio Arcara
Convolutional neural networks (CNNs) are a class of artificial neural networks (ANNs). Since the early 2010s, they have been widely adopted as models of primate vision and classifiers of neuroimaging data, becoming relevant for a wealth of neuroscientific fields. However, the majority of neuroscience researchers come…
Knut Rand, Ivar Grytten, Milena Pavlovic, Chakravarthi Kanduri + 1 more
Python is a popular and widespread programming language for scientific computing, in large part due to the powerful array programming library NumPy, which makes it easy to write clean, vectorized and efficient code for handling large datasets. A challenge with using array programming for biological data is that the…
Vincent Noël, Aurélien Naldi, Laurence Calzone, Loic Paulevé + 1 more
This tutorial provides stepwise instructions to install the 20 tools integrated in the CoLoMoTo software suite, to develop reproducible dynamical analyses of logical models of complex biological molecular networks. The tutorial specifically focuses on the analysis of a previously published model of the regulatory…