Books by "M. G. White"
2 books found
Themes: Realistic Fiction, Rural, Drug Addiction, Immigration, Fathers and Sons, College, Teen, Young Adult, Emergent Reader, Chapter Book, Hi-Lo, Hi-Lo Books, Hi-Lo Solutions, High-Low Books, Hi-Low Books, ELL, EL, ESL, Struggling Learner, Struggling Reader, Special Education, SPED, Newcomers, Reading, Learning, Education, Educational, Educational Books. Diego is determined to escape his small town where animals far outnumber people. He wants to go to art school, even though his father thinks an artistês life is a road to nowherehe didnêt come to the U.S. so his son could become a starving artist. Itês Diegoês dream, and he slowly saves for his future by dealing weed, which is easy to come by in the Emerald Triangle. Heês the dealer everyone turns to at school, but he refuses to deal in the hard stuff, like meth. His girlfriendês entire family is addicted to drugs; so heês seen its destructive power. From the Great Plains to the borderlands to the Mississippi Delta, rural America is struggling. The population is shrinking. And the economy is shifting away from agriculture. Without a safety net, rural families struggle with depression, drug abuse, alcoholism, and other problems. Gravel Road Rural addresses the contemporary issues affecting rural America in an unflinching way.
Machine Learning Approaches for Predicting AIDS Virus Infection
by Maanasa M.G., Ananya S. Padasalgi, Amrutha B.T., Smrithi R. Holla
2024 · GRIN Verlag
Academic Paper from the year 2024 in the subject Computer Science - Bioinformatics, grade: 1.5, , course: Biotechnology, language: English, abstract: This review investigates the use of machine learning approaches, notably Random Forest and Neural Network classifiers, in the context of AIDS classification and digit identification using the MNIST dataset. The paper compares the performance of a Random Forest classifier and a Multi-Layer Perceptron (MLP) neural network on an AIDS classification dataset, emphasizing the significance of feature scaling and the impact of model design on classification accuracy. The Random Forest model was used to determine feature relevance, and the MLP classifier was trained and tested for accuracy in categorizing the binary outcome of HIV infection.