brianferrell787

ARIMA-model-and-report-for-predicting-stock-prices

Creating and evaluating ARIMA forecasts for the stock CDW (Report included)

BERTLiterature

This contains an annotated bibliography and a literature review examining the robustness of BERT for text classification tasks and how to improve it. This stuff is pretty cool to me and I am still slowly learning, so maybe these resources can help you out with your own NLP text classification tasks!

Classifying-community-engaged-research-with-transformer-based-models

Novel approach to identifying and categorizing community-engaged studies by applying attention-based deep learning models to human subjects protocols

Hyperparameter-tuning-deep-learning-text-classification-model-using-Talos

Talos is made for data scientists and data engineers that want to remain in complete control of their Keras models, but are tired of mindless parameter hopping and confusing optimization solutions that add complexity instead of reducing it. Within minutes, without learning any new syntax, Talos allows you to configure, perform, and evaluate hyperparameter optimization experiments that yield state-of-the-art results across a wide range of prediction tasks. Talos provides the simplest and yet most powerful available method for hyperparameter optimization with Keras.

Interactive-Word-Embedding-Projector-from-Google

Word Embeddings using Google's embedding projector

Predicting-grades-using-Machine-Learning-models-w-report-

Built predictive models for final grades using statistical learning methods (Report included)

Predicting-Heart-Disease-using-PCA-in-R

This was a school project for my machine learning algorithms class to apply machine learning methods to a dataset to develop predictive models. The project was intended to give experience in applying machine learning methods for data analysis, tuning paramters, and communicating results. class.

Survey-of-data-mining-concepts

Describes a survey of literature surrounding knowledge discovery and data mining concepts, tools and methods.

Time-Series-Analysis-forecasting-with-ARIMA-in-google-colab

This was a school project to choose a dataset and software to build a forecasting model using whatever method we learned in class

Visualizing-attention-layer-in-text-classification-deep-learning-algorithm

So recently I have finished creating a prototype algorithm on a really small dataset that can detect the gradients of a newly created 5-level community engaged research heuristic. This model has a custom attention layer added in and I have found that visualizing this layer can actually help see what words are important and what words are not.

brianferrell787/Visualizing-attention-layer-in-text-classification-deep-learning-algorithm

So recently I have finished creating a prototype algorithm on a really small dataset that can detect the gradients of a newly created 5-level community engaged research heuristic. This model has a custom attention layer added in and I have found that visualizing this layer can actually help see what words are important and what words are not.

brianferrell787/Classifying-community-engaged-research-with-transformer-based-models

Novel approach to identifying and categorizing community-engaged studies by applying attention-based deep learning models to human subjects protocols

brianferrell787/Hyperparameter-tuning-deep-learning-text-classification-model-using-Talos

Talos is made for data scientists and data engineers that want to remain in complete control of their Keras models, but are tired of mindless parameter hopping and confusing optimization solutions that add complexity instead of reducing it. Within minutes, without learning any new syntax, Talos allows you to configure, perform, and evaluate hyperparameter optimization experiments that yield state-of-the-art results across a wide range of prediction tasks. Talos provides the simplest and yet most powerful available method for hyperparameter optimization with Keras.

brianferrell787/Predicting-Heart-Disease-using-PCA-in-R

This was a school project for my machine learning algorithms class to apply machine learning methods to a dataset to develop predictive models. The project was intended to give experience in applying machine learning methods for data analysis, tuning paramters, and communicating results. class.

brianferrell787/Time-Series-Analysis-forecasting-with-ARIMA-in-google-colab

This was a school project to choose a dataset and software to build a forecasting model using whatever method we learned in class

brianferrell787/ARIMA-model-and-report-for-predicting-stock-prices

Creating and evaluating ARIMA forecasts for the stock CDW (Report included)

brianferrell787/BERTLiterature

This contains an annotated bibliography and a literature review examining the robustness of BERT for text classification tasks and how to improve it. This stuff is pretty cool to me and I am still slowly learning, so maybe these resources can help you out with your own NLP text classification tasks!

brianferrell787/Data-augmentation-for-text-data-nlpaug

To help fix a small dataset problem I implemented data augmentation techniques to synthetically increase the amount of data we have. I then trained the deep learning network on the augmented data and not the original set(that became the test set)

brianferrell787/Interactive-Word-Embedding-Projector-from-Google

Word Embeddings using Google's embedding projector

brianferrell787/Predicting-grades-using-Machine-Learning-models-w-report-

Built predictive models for final grades using statistical learning methods (Report included)

brianferrell787/Survey-of-data-mining-concepts

Describes a survey of literature surrounding knowledge discovery and data mining concepts, tools and methods.

brianferrell787/FinRL

FinRL: Financial Reinforcement Learning. 🔥

brianferrell787/INFO-691-22

brianferrell787/nlpaug

Data augmentation for NLP

brianferrell787/Postgres-DB-with-Docker

https://community.vcu.edu/

brianferrell787/profit-naacl

Code for PROFIT: Quantitative Day Trading From Natural Language Using Reinforcement Learning at NAACL 2021

brianferrell787/simpletransformers

Transformers for Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI

brianferrell787/StockDecisisionTree

brianferrell787/stocknet-dataset

A comprehensive dataset for stock movement prediction from tweets and historical stock prices.

brianferrell787/Tensorboard-graph-problem-fixed-for-Google-Colab

I wanted to make a simple graph visualizing the architecture of my text classification algorithm and I came across Tensorboard graphs and thought I might give it a try. Sadly I kept getting an error that looks like this: