kstrassheim

active-learning-with-deep-learning-for-nlp

We present our concept of a new type of Active-Learning for Deep Learning with NLP text classification and experimentally prove its performance against Random Sampling as well as its runtime performance on the Security Threat dataset from CySecAlert. These new Active Learning algorithms are based on Sentence-BERT and BERTopic clustering algorithms with allow us to generate fixed length tokens for whole sentences to make them comparable to each other. Further the Tokens are Clustered using K-Means or HDBScan to get diverse clusters to pick the samples out of them.

breathraterecognition

By using capacitive pressure sensors inside a seat this application is able to retreive the signal and measure the respiratory rate out of its sinus frequency, by using 3 different algorithms (Discrete Fourier Transformation, Continuous Cut Count, Discrete single period)

chest-xray-pneumonia

Coursera-Deep-Learning

My notes / works on deep learning from Coursera

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

datawarehouse-crawler

This is a content and schema crawler tool to receive, update and import various kinds of data into a Onprem or Cloud based SQLServer or Azure-Synapse-Analysis (Azure Datawarehouse SQLServer). As source it supports SQLServer Tables, ODATA Endpoints, CSV Files or Excel Files. For multiple sources it can run in parallel mode where it would make a thread for each connection. The speciality of this crawler is that it creates the target tables by himself using the additional info from source.json. In case of Azure-Synapse-Analysis it would estimate the distribution type and keys. The syncing works completely without SQL Transactions by using a consistency correction algorithm for very frequent fact tables. There are 5 Syncing Algorithms (see Manual/Insert) which can be selected as well as one Update Algorithm.

django_react_reference_webapp

explain-ai

This web-app shows the functionality of the model-agnostic explainable-ai engine LIME on 3 common deep learning text classifiers (BERT, LSTM, TFIDF-NN) for fake news detection.

geo-pointer

This app transforms and shows geo-data points (lon, lat) for selected countries on custom mercator maps (pixels)

picture-gallery

A simple whiteboard for pictures to enable cooperative working. The purpose was to show the possibility of an intuitive, real-time, responsive and progressive web-application without buttons and text.

kstrassheim/active-learning-with-deep-learning-for-nlp

We present our concept of a new type of Active-Learning for Deep Learning with NLP text classification and experimentally prove its performance against Random Sampling as well as its runtime performance on the Security Threat dataset from CySecAlert. These new Active Learning algorithms are based on Sentence-BERT and BERTopic clustering algorithms with allow us to generate fixed length tokens for whole sentences to make them comparable to each other. Further the Tokens are Clustered using K-Means or HDBScan to get diverse clusters to pick the samples out of them.

kstrassheim/datawarehouse-crawler

This is a content and schema crawler tool to receive, update and import various kinds of data into a Onprem or Cloud based SQLServer or Azure-Synapse-Analysis (Azure Datawarehouse SQLServer). As source it supports SQLServer Tables, ODATA Endpoints, CSV Files or Excel Files. For multiple sources it can run in parallel mode where it would make a thread for each connection. The speciality of this crawler is that it creates the target tables by himself using the additional info from source.json. In case of Azure-Synapse-Analysis it would estimate the distribution type and keys. The syncing works completely without SQL Transactions by using a consistency correction algorithm for very frequent fact tables. There are 5 Syncing Algorithms (see Manual/Insert) which can be selected as well as one Update Algorithm.

kstrassheim/explain-ai

This web-app shows the functionality of the model-agnostic explainable-ai engine LIME on 3 common deep learning text classifiers (BERT, LSTM, TFIDF-NN) for fake news detection.

kstrassheim/picture-gallery

A simple whiteboard for pictures to enable cooperative working. The purpose was to show the possibility of an intuitive, real-time, responsive and progressive web-application without buttons and text.

kstrassheim/breathraterecognition

By using capacitive pressure sensors inside a seat this application is able to retreive the signal and measure the respiratory rate out of its sinus frequency, by using 3 different algorithms (Discrete Fourier Transformation, Continuous Cut Count, Discrete single period)

kstrassheim/chest-xray-pneumonia

kstrassheim/Coursera-Deep-Learning

My notes / works on deep learning from Coursera

kstrassheim/coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

kstrassheim/django_react_reference_webapp

kstrassheim/geo-pointer

This app transforms and shows geo-data points (lon, lat) for selected countries on custom mercator maps (pixels)

kstrassheim/node-auth-form

kstrassheim/node-auth-new

kstrassheim/react-test-app

kstrassheim/self_build_predictors

some self build data science predictors

kstrassheim/usermanagement-web

The frontend for the usermanagement web

kstrassheim/web-test

Simple test app for webpack configurations