Vanessa Grass

Deep Learning Enthusiast interested in Neuroscience, Biotech, and Longevity research

about me

 present training epoch: optimizing and updating artificial neural network weights, including in my own biological neural network.

 recent training epoch: graduated from the University of New Haven's M.S. in Data Science program.

 past training epochs: biology/premed, digital product design, now data science. There are indeed some non-linearities in my academic and professional background :)

 current local minima: computer vision, NLP, reinforcement learning, and potential applications of AI in relation to creative applications, biotechnology, and healthcare sectors.

 favorite architectures: variational autoencoders and generative adversarial networks.

 fascinated by: computational neuroscience, brain-computer interfaces, and epigenetics.

 tools: python, scikit-learn, Keras, TensorFlow, and actively learning PyTorch.