short_text_analyzer

The Short-Text Analyzer is created to help analyze the open-ended survey response which usually has less than three sentences. The analysis includes topic modeling, sentiment analysis, and visualization. This topic modeling was done using pre-trained representations of language, namely BERT, combine with the clustering algorithm.

spark

Apache Spark - A unified analytics engine for large-scale data processing

spark-docker

spark-standalone-cluster-on-docker

Learn Apache Spark in Scala, Python (PySpark) and R (SparkR) by building your own cluster with a JupyterLab interface on Docker. :zap:

spring2020

Spring 2020 UMBC data 601

stanford_alpaca

Code and documentation to train Stanford's Alpaca models, and generate the data.

stat_rethinking_2024

statsforecast

Lightning ⚡️ fast forecasting with statistical and econometric models.

statsmodels

Statsmodels: statistical modeling and econometrics in Python

survey-topic-modelling

NLP on Educator Survey Open Ended Comments

t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

tad

This is the public repository for my quarter long text as data course

taipy

Turns Data and AI algorithms into production-ready web applications in no time.

tensorflow-advanced-techniques-specialization

tensorflow-examples

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

tensorflow_cookbook

Code for Tensorflow Machine Learning Cookbook

testing-ml

🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.

tf-tabnet

A Tensorflow 2.0 implementation of TabNet.

the-elements-of-statistical-learning-python-notebooks

A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book

themarketingtechnologist

timeseriesforecasting-deeplearning

An experiemtal review on deep learning architectures for time series forecasting

topic-modelling

training-data-analyst

Labs and demos for courses for GCP Training (http://cloud.google.com/training).

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

transformers-for-nlp-2nd-edition

Under the hood working of transformers, fine-tuning GPT-3 models, DeBERTa, vision models, and the start of Metaverse, using a variety of NLP platforms: Hugging Face, OpenAI API, Trax, and AllenNLP

tslearn

A machine learning toolkit dedicated to time-series data

tsmoothie

A python library for time-series smoothing and outlier detection in a vectorized way.

uf-intro-to-programming

University of Florida Audience Analytics Introduction to Programming with Data course

unet-aerialsegmentation

A PyTorch implementation of U-Net for aerial imagery semantic segmentation.

unix-shell

A simple implementation of the Unix Shell with Java - including Directory, Text, Redirection, Piping, and Background Commands