Hani Jandali is a data science graduate with experience teaching machine learning and deep learning concepts as a Data Science Teaching Assistant at Dominican University of California. He has also completed a Machine Lea…
Hani Jandali is a data science graduate with experience teaching machine learning and deep learning concepts as a Data Science Teaching Assistant at Dominican University of California. He has also completed a Machine Learning Engineer Internship and a Research Assistant role, with skills in Python, SQL, machine learning, deep learning, and data science tools and libraries.
Created course materials and assignments to communicate core concepts in data science to classes of 22 students.
Taught core supervised and unsupervised machine learning topics, including regression models, support vector machines, decision trees, random forests, clustering algorithms, gaussian mixtures, and markov chains.
Further taught deep learning neural networks, including artificial, recurrent, convolutional, and adversarial networks.
Introduced implementation of fundamental libraries, including Scikit-Learn, Tensorflow, Keras, and PyTorch.
Implemented a probabilistic recommendation system to underlie the networking potential of the application.
Created a multi-layer deep neural network feeding in JSON data of hundreds of users, generating user-user recommendations through keywords indicating possible similarities in interests and profession, with scores above 45% receiving a potential status, and scores above 68% receiving a recommended friend status on the website.
Conducted bioinformatics research on signal transduction pathways activated and suppressed within arabidopsis under whitefly infestation for isolation of resistant gene markers on the fourth chromosome to transplant into alfalfa.
Implemented a probabilistic recommendation system to underlie the networking potential of the application.
Created a multi-layer deep neural network feeding in JSON data of hundreds of users, generating user-user recommendations through keywords indicating possible similarities in interests and profession, with scores above 45% receiving a potential status, and scores above 68% receiving a recommended friend status on the website.
Conducted bioinformatics research on signal transduction pathways activated and suppressed within arabidopsis under whitefly infestation for isolation of resistant gene markers on the fourth chromosome to transplant into alfalfa.
● Created course materials and assignments to communicate core concepts in data science to classes of 22 students.
● Taught core supervised and unsupervised machine learning topics, including regression models, support vector
machines, decision trees, random forests, clustering algorithms, gaussian mixtures, and markov chains.
● Further taught deep learning neural networks, including artificial, recurrent, convolutional, and adversarial networks.
● Introduced implementation of fundamental libraries, including Scikit-Learn, Tensorflow, Keras, and PyTorch.
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