By Akshay Shah, Harry Chalfin and Connor Uzzo

Executive Summary

Since our second blog post, we adjusted and tuned our model and comfortably passed 80% validation accuracy with our final implementation (83.5%). This was achieved by simplifying our model’s head, using a stronger base, and implementing early stopping to halt the training before overfitting. Our new model head (Figure 1) simply takes the output of the base, passes it through a global average pooling layer, and flows directly into the 5 node dense layer that represents class prediction probabilities.

Figure 1: Code for creating model head in Keras

Initially, we tried using Google Colab for this effort but had some trouble…

By Akshay Shah, Harry Chalfin, and Connor Uzzo

Since our initial post in February (see, we have been in the process of building a convolutional neural network (CNN) that can identify different cassava leaf diseases based on a digital image of the leaves. This has involved rethinking some of our coding strategy. Some of these changes were to overcome unforeseen issues issues like limited data storage and long run times, while others, like introducing data augmentation, were made to improve the overall potential of the model.


We chose to switch from implementing our model in Google Colab to instead…

By Akshay Shah, Harry Chalfin, and Connor Uzzo

Cassava is an important crop in many African households due to its resilience against harsh climates. It is susceptible to several viral diseases however, and diagnosing these diseases requires assistance from government trained agriculture experts. If a deep learning model could be deployed capable of recognizing these diseases based on digital images, farmers could decide on treatment for their cassava plants without waiting and paying for one of these experts. Using the Kaggle Cassava Leaf Disease Classification dataset and Python’s Tensorflow package, we are building such a pipeline. So far the highest…

Image from [7]

In 1973, financial mathematicians Fischer Black and Myron Scholes published an academic paper titled “The Pricing of Options and Corporate Liabilities”, which contained what would end up becoming one of the most pivotal equations in all of mathematical finance, the Black-Scholes model[1]. The model is a stochastic-partial differential equation used to assign a value to a European style option, a type of asset that allows the holder to buy or sell a stock at its current price regardless of its future behavior. …

Connor Uzzo

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