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$20 USD / hora
Bandera de MALAYSIA
melaka, malaysia
$20 USD / hora
Aquí son las 5:10 a. m.
Se unió el octubre 7, 2012
0 recomendaciones

Nur Aishah A.

@nuraishahrazak

 5,0 (1 comentario)
2,7
2,7
100%
100%
$20 USD / hora
Bandera de MALAYSIA
melaka, malaysia
$20 USD / hora
100 %
Trabajos finalizados
100 %
Dentro del presupuesto
100 %
A tiempo
N/A
Tasa de recontratación

Software Developer . Machine Learning . AI

Hi there! I would like to help you translate your business needs into solutions. With more than 10 years experience in Software Development and IT Consulting, I have a knack of not just developing Software but also getting very good understanding of business workflows and coming up with end-to-end solutions. I have worked on numerous Desktop Applications (Windows Forms, WPF, WCF web services) and Web Applications (.NET MVC, .NET Core, Backbone, Angular, Azure, GCP, Flask) (hosted both on-prem and on cloud) in my professional life. I am also experienced in Artificial Intelligence - specifically in Computer Vision and Deep Learning. Do drop me a note if you'd like to discuss possible opportunities. I'd be happy to have a quick chat with you.
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Portafolio

10345478
These are data analysis and visualizations I developed for my research that looks at one facet of predicting the spread of Covid-19 cases by looking at the relationship between government policies being put in place and the total number of cases by utilizing Machine Learning techniques.
Data Analysis & Visualization for Covid19 Government Measure
These are data analysis and visualizations I developed for my research that looks at one facet of predicting the spread of Covid-19 cases by looking at the relationship between government policies being put in place and the total number of cases by utilizing Machine Learning techniques.
Data Analysis & Visualization for Covid19 Government Measure
These are data analysis and visualizations I developed for my research that looks at one facet of predicting the spread of Covid-19 cases by looking at the relationship between government policies being put in place and the total number of cases by utilizing Machine Learning techniques.
Data Analysis & Visualization for Covid19 Government Measure
These are data analysis and visualizations I developed for my research that looks at one facet of predicting the spread of Covid-19 cases by looking at the relationship between government policies being put in place and the total number of cases by utilizing Machine Learning techniques.
Data Analysis & Visualization for Covid19 Government Measure
10305823
This is a Flask App for analysing Malay Language Morphology. The main advantage of this analyzer is the ability to morph a word into a noun or verb by adding prefixes to the word. Other advantages of the analyzer I created is that it considers edge cases like the word ‘ajar’ that has different prefix to use (‘pe-‘) and one syllable word like ‘bom’ that uses ‘menge-‘ and ‘penge-‘ prefix. This analyzer is also able to change a word into a intransitive verb e.g. ‘berlari’ by prefixing ‘ber-‘ to the input word.
NLP: Malay Language Morphology Analyser
This is a Flask App for analysing Malay Language Morphology. The main advantage of this analyzer is the ability to morph a word into a noun or verb by adding prefixes to the word. Other advantages of the analyzer I created is that it considers edge cases like the word ‘ajar’ that has different prefix to use (‘pe-‘) and one syllable word like ‘bom’ that uses ‘menge-‘ and ‘penge-‘ prefix. This analyzer is also able to change a word into a intransitive verb e.g. ‘berlari’ by prefixing ‘ber-‘ to the input word.
NLP: Malay Language Morphology Analyser
10305803
Ontology Project: Companies' Named Entity Extraction
10305798
The thesis seeks to demonstrate how transfer learning from macro-expression database in a lightweight network can achieve high Micro-Expression Recognition (MER). The proposed MER model is developed from truncated EfficientNet-B0 model that is pre-trained on a macro-expression database before fine-tuned on the CDE dataset. A simple algorithm-tuning that manipulates the loss function is suggested to deal with the imbalanced dataset. The resulting model is considerably small with just 867K parameters. Experimental results using Leave-One-Subject-Out cross validation show substantial performance increase compared to the state-of-the-arts with UF1 score of 0.98 and UAR score of 1.77. The images attached shows the pre-processing steps done to a sample of the dataset.
Thesis: Lightweight Micro-Expression Recognition
The thesis seeks to demonstrate how transfer learning from macro-expression database in a lightweight network can achieve high Micro-Expression Recognition (MER). The proposed MER model is developed from truncated EfficientNet-B0 model that is pre-trained on a macro-expression database before fine-tuned on the CDE dataset. A simple algorithm-tuning that manipulates the loss function is suggested to deal with the imbalanced dataset. The resulting model is considerably small with just 867K parameters. Experimental results using Leave-One-Subject-Out cross validation show substantial performance increase compared to the state-of-the-arts with UF1 score of 0.98 and UAR score of 1.77. The images attached shows the pre-processing steps done to a sample of the dataset.
Thesis: Lightweight Micro-Expression Recognition
The thesis seeks to demonstrate how transfer learning from macro-expression database in a lightweight network can achieve high Micro-Expression Recognition (MER). The proposed MER model is developed from truncated EfficientNet-B0 model that is pre-trained on a macro-expression database before fine-tuned on the CDE dataset. A simple algorithm-tuning that manipulates the loss function is suggested to deal with the imbalanced dataset. The resulting model is considerably small with just 867K parameters. Experimental results using Leave-One-Subject-Out cross validation show substantial performance increase compared to the state-of-the-arts with UF1 score of 0.98 and UAR score of 1.77. The images attached shows the pre-processing steps done to a sample of the dataset.
Thesis: Lightweight Micro-Expression Recognition
5047981
Data management web tool with Azure components: - Angular pages for editing data - Bulk data upload to Azure - User profile management - All data integration are using .NET core web API - UX/UCD for workflows and page designs - CI/CD for TFS deployment
EMSDB.IO web application
5047965
Ergonomics Assessment Tracking Tool (EATT): - Allows users to submit ergonomics self-assessments - Allows Ergo Contacts to view the submitted self-assessments and input his/her observations and action items - Allows tracking of observations and action items - Dashboard to view critical cases at a glance for Ergo Contact
EATT Web application
10345478
These are data analysis and visualizations I developed for my research that looks at one facet of predicting the spread of Covid-19 cases by looking at the relationship between government policies being put in place and the total number of cases by utilizing Machine Learning techniques.
Data Analysis & Visualization for Covid19 Government Measure
These are data analysis and visualizations I developed for my research that looks at one facet of predicting the spread of Covid-19 cases by looking at the relationship between government policies being put in place and the total number of cases by utilizing Machine Learning techniques.
Data Analysis & Visualization for Covid19 Government Measure
These are data analysis and visualizations I developed for my research that looks at one facet of predicting the spread of Covid-19 cases by looking at the relationship between government policies being put in place and the total number of cases by utilizing Machine Learning techniques.
Data Analysis & Visualization for Covid19 Government Measure
These are data analysis and visualizations I developed for my research that looks at one facet of predicting the spread of Covid-19 cases by looking at the relationship between government policies being put in place and the total number of cases by utilizing Machine Learning techniques.
Data Analysis & Visualization for Covid19 Government Measure
10305823
This is a Flask App for analysing Malay Language Morphology. The main advantage of this analyzer is the ability to morph a word into a noun or verb by adding prefixes to the word. Other advantages of the analyzer I created is that it considers edge cases like the word ‘ajar’ that has different prefix to use (‘pe-‘) and one syllable word like ‘bom’ that uses ‘menge-‘ and ‘penge-‘ prefix. This analyzer is also able to change a word into a intransitive verb e.g. ‘berlari’ by prefixing ‘ber-‘ to the input word.
NLP: Malay Language Morphology Analyser
This is a Flask App for analysing Malay Language Morphology. The main advantage of this analyzer is the ability to morph a word into a noun or verb by adding prefixes to the word. Other advantages of the analyzer I created is that it considers edge cases like the word ‘ajar’ that has different prefix to use (‘pe-‘) and one syllable word like ‘bom’ that uses ‘menge-‘ and ‘penge-‘ prefix. This analyzer is also able to change a word into a intransitive verb e.g. ‘berlari’ by prefixing ‘ber-‘ to the input word.
NLP: Malay Language Morphology Analyser
10305803
Ontology Project: Companies' Named Entity Extraction
10305798
The thesis seeks to demonstrate how transfer learning from macro-expression database in a lightweight network can achieve high Micro-Expression Recognition (MER). The proposed MER model is developed from truncated EfficientNet-B0 model that is pre-trained on a macro-expression database before fine-tuned on the CDE dataset. A simple algorithm-tuning that manipulates the loss function is suggested to deal with the imbalanced dataset. The resulting model is considerably small with just 867K parameters. Experimental results using Leave-One-Subject-Out cross validation show substantial performance increase compared to the state-of-the-arts with UF1 score of 0.98 and UAR score of 1.77. The images attached shows the pre-processing steps done to a sample of the dataset.
Thesis: Lightweight Micro-Expression Recognition
The thesis seeks to demonstrate how transfer learning from macro-expression database in a lightweight network can achieve high Micro-Expression Recognition (MER). The proposed MER model is developed from truncated EfficientNet-B0 model that is pre-trained on a macro-expression database before fine-tuned on the CDE dataset. A simple algorithm-tuning that manipulates the loss function is suggested to deal with the imbalanced dataset. The resulting model is considerably small with just 867K parameters. Experimental results using Leave-One-Subject-Out cross validation show substantial performance increase compared to the state-of-the-arts with UF1 score of 0.98 and UAR score of 1.77. The images attached shows the pre-processing steps done to a sample of the dataset.
Thesis: Lightweight Micro-Expression Recognition
The thesis seeks to demonstrate how transfer learning from macro-expression database in a lightweight network can achieve high Micro-Expression Recognition (MER). The proposed MER model is developed from truncated EfficientNet-B0 model that is pre-trained on a macro-expression database before fine-tuned on the CDE dataset. A simple algorithm-tuning that manipulates the loss function is suggested to deal with the imbalanced dataset. The resulting model is considerably small with just 867K parameters. Experimental results using Leave-One-Subject-Out cross validation show substantial performance increase compared to the state-of-the-arts with UF1 score of 0.98 and UAR score of 1.77. The images attached shows the pre-processing steps done to a sample of the dataset.
Thesis: Lightweight Micro-Expression Recognition
5047981
Data management web tool with Azure components: - Angular pages for editing data - Bulk data upload to Azure - User profile management - All data integration are using .NET core web API - UX/UCD for workflows and page designs - CI/CD for TFS deployment
EMSDB.IO web application
5047965
Ergonomics Assessment Tracking Tool (EATT): - Allows users to submit ergonomics self-assessments - Allows Ergo Contacts to view the submitted self-assessments and input his/her observations and action items - Allows tracking of observations and action items - Dashboard to view critical cases at a glance for Ergo Contact
EATT Web application

Comentarios

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5,0
$225,00 USD
Test and edit Python codes
She delivered great work with minimum instruction! Compled all tasks in 1/2 time allowed. Well communication, will hire again!
Python
Machine Learning (ML)
Big Data
NLP
H
Bandera de Hoang N.
@hngu178
•
hace 2 años

Experiencia

Advisor

Techylimpics
jun 2022 - Presente
• Advises and oversees on training materials and competition details such as the activities, judging criteria and source materials for the Artificial Intelligence competition track

Graduate student

UKM
feb 2020 - mar 2022 (2 años, 1 mes)
• Masters study in Artificial Intelligence with thesis focusing on automatic and lightweight micro-expression recognition model utilizing transfer learning from macro-expression database. The proposed model is based on EfficientNet-B0 model that is truncated with only 867k parameters. LOSO cross validation has surpassed the state-of-the-arts with UF1 score of 0.98 and UAR score of 1.77. • NLP project : N-Gram tokenizer from scratch

Technical Lead

AirAsia
mar 2021 - dic 2021 (9 meses, 1 día)
- Lead, managed and groom requirements for the Health Travel Pass project - Worked on enhancing counter check-in application (Angular/ GCP / .NET API) to include vaccination checks etc - Built web application to capture, annotate, store and retrieve travel documents (ReactJS / NodeJS)

Educación

MSc Artificial Intelligence

Universiti Kebangsaan Malaysia, Malaysia 2020 - 2022
(2 años)

BE IT (Software Engineering)

University of Melbourne, Australia 2005 - 2010
(5 años)

Contacta Nur Aishah A. sobre tu trabajo

Inicia sesión para comentar cualquier detalle por chat.

Verificaciones

Freelancer preferente
Identidad verificada
Pago verificado
Teléfono verificado
Email verificado
Facebook conectado

Certificaciones

c-sharp-prog-1.png C# Programming 1 90%
us_eng_1.png US English 1 85%

Principales habilidades

Python 1
Machine Learning (ML) 1
.NET
Cloud Computing
C# Programming

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