Yogesh Gupta’s Post

Applied Time Series Analysis Course ❤️ If you are looking to learn the foundation of time series analysis and forecasting, I recommend checking the Applied Time Series Analysis course from the University of Washington. The course by Prof Eli Holmes, Prof. Eric Ward, and Prof. Mark Scheuerell focuses on the foundation of time series analysis with applications for environmental science and covers topics such as: ✅ Time series decomposition ✅ Covariance and correlation ✅ Autoregressive (AR) models ✅ Moving average (MA) models ✅ Forecasting with ARIMA models ✅ Univariate state-space models ✅ Dynamic linear models ✅ Hidden Markov models The course code examples are in R. Lectures 📽️: https://lnkd.in/gb27hMaN Course info 📖: https://lnkd.in/g--xfSXx #datascience #timeseries #forecasting #rstats

Excited to share a class research project from my spring semester (2024), on Machine Learning for Flux Estimation, as part of my work at the University at Albany! 🌍✨ In this project, I implemented the Monin-Obukhov similarity theory to analyze sensible heat flux using data from the VOOR and BELL stations in NY state. The motivation for this project was to predict the heat flux using an ANN and then comparing it to a multiple linear regression model for better accuracy estimation. https://lnkd.in/eV6zZ8tZ Check out the full presentation for more details! 🔍📊 #MachineLearning #DataScience #Research #HeatFlux #ClimateData

Title: Iris Flower Classification: Unveiling the Power of Machine Learning Description: Excited to present my latest project: Iris Flower Classification! 🌸🔍 Using the classic Iris dataset, I trained a machine learning model to accurately classify Iris flowers into their respective species based on sepal and petal measurements. Join me as we explore the fascinating world of introductory classification tasks! #codsoft #datascience #machinelearning #irisclassification

As promised, we are back with another exciting seminar featuring a fantastic topic presented by an outstanding speaker. 💫 e16 Classes Please keep your calendars clear and join us for this event! Topic : "Breakups are hard: Unless you are an Unsupervised Model" Date : 25th September, 2024 Time : 8:00 pm Speaker : Sayan Chaki Registration Link: https://lnkd.in/g7jTyi8D You will receive an invitation email on September 24th. #UnsupervisedLearning #machinelearning #datascience #artificialintelligence #mathematics #statistics #computerscience

It was a pleasure to present the first academic poster of my PhD journey at the 38th International Workshop on Statistical Modelling last week in Durham, United Kingdom. Attendees found the incorporation of novel and unusual methods and remote sensing data to be quite refreshing. The full work will be published in the upcoming Springer volume Developments in Statistical Modelling, part of the series Contributions to Statistics. #GaussianProcess #Boosting #XGBoost #GPBoost #SatelliteData #RemoteSensing #FoodSecurity #ClimateChange #MachineLearning #ArtificialIntelligence #SpatialStatistics #StatisticalModelling #IWSM2024

Check this out! Learn how researchers turned to machine learning to predict a hurricane’s potential for intensification potential in the Atlantic and Pacific oceans. #machinelearning #MATLAB https://spr.ly/60499OUiR

🆕🎉 I’m proud to share that our recent work "Bayesian Transfer Learning for Artificially Intelligent Geospatial Systems: A Predictive Stacking Approach" is now out on arXiv. 🌍📊 We introduce a novel Bayesian Transfer Learning framework for AI-driven geospatial systems, enabling rapid and scalable spatial data analysis! 🌊🌿 We show its effectiveness in climate science applications. Accelerating uncertainty quantification and robust inference for large-scale problems. ✅📌Thanks to my co-author Sudipto Banerjee for all the work and the unique mentorship! 📢🔗Check it out: [ https://lnkd.in/dg87Myi8 ] #ArtificialIntelligence #GeospatialSystems #BayesianMethods #TransferLearning #PredictiveStacking #ClimateScience #DataScience #SpatialDataAnalysis 🤖😁 Disclaimer: AI-generated image (this is how DALL-E "sees" our work)

🔔🔔🔔 #MDPIfutureinternet [New Published Papers in 2024] Title: Predicting the Duration of Forest Fires Using Machine Learning Methods Authors: Constantina Kopitsa, ioannis tsoulos, Vasileios Charilogis and Athanassios Stavrakoudis Please read at: https://lnkd.in/gmR5ABdH Keywords: forest fires; #machinelearning; #neuralnetworks; #decisiontrees via Future Internet MDPI

Hello connection!! successfully completed ..🌟 Task 1 : Iris flower has three species: setosa, versicolor, and virginica, which differs according to their measurements. Now assume that you have the measurements of the iris flowers according to their species, and here your task is to train a machine learning model that can learn from the measurements of the iris species and classify them. #oasisinfobyte

🔔🔔🔔 #MDPIfutureinternet [New Published Papers in 2024] Title: Predicting the Duration of Forest Fires Using Machine Learning Methods Authors: Constantina Kopitsa, ioannis tsoulos, Vasileios Charilogis and Athanassios Stavrakoudis Please read at: https://lnkd.in/g5di_zaE Keywords: forest fires; #machinelearning; #neuralnetworks; #decisiontrees