• Mitalbahen Chavada
• Prof. Mehul Patel
• Prof. Ankur J. Goswami
• Prof. Jayesh M. Mevada
• Prof. Govind V. Patel

This survey takes a close look at how machine learning is changing the way we predict landslides. Landslides can be really dangerous, so it's crucial to have effective ways to predict when they might happen. The survey compares machine learning to more traditional methods and puts the different machine learning models into three groups: supervised, unsupervised, and en-semble methods. The survey also explores where we get the data from, how we pick out the important parts, and which case studies show that machine learning is good at predicting landslides. It talks about how we measure if the predictions are accurate, the problems we still need to solve, and the things we need to be careful about, like ethical issues. In the end, the survey looks ahead to what's next and says that machine learning is making a big difference in making landslide predictions more accurate. This helps us manage the risks better and handle disasters more effectively

Landslide prediction, Machine learning, Decision Tree, Random Forests, Deep Learning, SVM

"Predicting Landslide Using Machine Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 12, page no.f33-f40, December-2023, Available :http://www.jetir.org/papers/JETIR2312506.pdf

"Predicting Landslide Using Machine Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 12, page no. ppf33-f40, December-2023, Available at : http://www.jetir.org/papers/JETIR2312506.pdf