LauraAnn Migliore, Ph.D.’s Post

Here is the link to view a video recording of my presentation at the #2023TLC #UAGC #workforcedevelopment #generativeai #digitalskills #highereducation

I’m happy to share that I’ve obtained a new certification: Presenter at the 2023 Knowledge Without Boundaries (KWB) Summit from University of Phoenix!

Link to my video presentation at KWB 2023 Conference presented 10/12/2023 #KWB2023, #GenerativeAi, #MachineLearning, #UOPX,  #LLM, #SystematicLiteratureReview

KWB Summit is FREE and open to the PUBLIC, but you must register via the link below to attend. I will be presenting on the topic of producing an automated systematic literature review (SLR) using advanced artificial intelligence tools and methods to optimize the research process for current and aspiring scholars, practitioners, and leaders on Thursday 10/12/2023 at 1:00pm Phoenix / 4:00pm Eastern time in Session 7. #KWB2023 #UOPX #GenerativeAI #MachineLearning #SystematicLiteratureReview #LLM

Dr. LauraAnn Migliore presented at the Complexity, Informatics, and Cybernetics: IMCIC Conference for Trans-Disciplinary Communications (March 31, 2023) on "AI Collaborations in Higher Education to Improve Critical Thinking Skills." If your research skills are in #datascience #AI #generativeai for improving #criticalthinkingskills and #personalizedlearning and you are interested in working collaboratively on #researchprojects please contact me. #pioneering in #advancingtechnology for #highereducation

I enjoyed a fascinating learning experience in Artificial Intelligence (AI) with Deep Learning Great Learning #universityoftexas #greatlearning #powerahead #ai #deeplearning #datascience

I'm planning to attend the Google I/O annual developer conference featuring Google’s latest developer solutions, products, and technology. May 10, 2023 #kaggle #technology #developer #google #datascience

LauraAnn Migliore, Ph.D. has successfully completed a project on Twitter Sentiment Analysis for Airline Services to identify the sentiment from a tweet (positive, neutral, or negative) and gain deeper insights on airlines' customer satisfaction. Data was preprocessed (via tokenization, removal of special characters, punctuations, etc., and lemmatization). Applied count vectorizer and Tf-IDF vectorizer and fit the model using vectorized column with cross validation. Model was evaluated using confusion matrix and review of the top 40 features via word cloud plot. #HandsOnProject #Workingwithtext #Vectorization #Countvectorizer #TfIDFvectorizer #Sentimentanalysis #Parametertuning #Confusionmatrixbasedmodelevaluation  #MyGreatLearning #universityoftexas

LauraAnn Migliore, Ph.D. has successfully completed a project using Python to build several classification models via artificial neural networks (ANNs) to predict bank churn (customers leaving and joining another service provider) and to understand which aspects of service influenced a customer’s decision in this regard. The best model built included the #AdamOptimizer #AI #artificialneuralnetworks #Classificationmodels #MyGreatLearning #universityoftexas