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Nicolas G.

@nicolasgi

4,9
5
4,0
4,0
100%

Data and AI scientist

$35 USD / Heure
Drapeau de
France (5:00 AM)
Inscrit depuis le avril 25, 2024
$35 USD / Heure
I am a data analyst and AI engineer with a doctorat in signal processing. I also work on AI-generated music (any styles and texts in english or french).
Vérifications
Dans les temps
100 %
Dans le budget
100 %
Taux d'acceptation
100 %

Portfolio

Portfolio

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12183790
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11938088
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Modifications enregistrées
4.9 · 5 Reviews
Commentaires
A
Nicolas is amazing and very hard worker, he goes above and beyond what is required of him. I highly recommend anyone who is looking for a task / project to be done, and give Nicolas a chance. He will take in any task and go beyond what is expected of him, excelling in all the results and expectations of the task. This guy is a legend and is very good at what he does!
Andrei A.
@andrei693
Drapeau de
Melbourne, Australia
il y a 6 mois
Partager
C
Sports Data Scraping $210 USD
He is dedicated to the work to be done. Good communicator.
Andrei C.
@carabeleaandrei
Drapeau de
Arad, Romania
il y a 8 mois
Partager
T
Nicolas was very solution oriented in his approach to our problem, almost immediately understanding the ask and offering guidance. He was very thorough in ensuring we had in fact covered everything we wanted to look at, as a resulted he added additional value outside of his development skill. He was very timeous in his contribution and exhibited great integrity in our dealings.
Raymond P.
@TheStrelok
Drapeau de
Johannesburg, South Africa
il y a 9 mois
Partager
S
Great Python Programmer. Delivered the script as required.
Sergi A.
@sgegi87
Drapeau de
Tbilisi, Georgia
il y a 10 mois
Partager
Avatar de l'utilisateur
"great communication, no problems at all, kind person finished job so fast without any problems Highly recommended"
Mariam T.
@AMariamo
Drapeau de
Tkibuli, Georgia
il y a 10 mois
Partager
Expérience
Capgemini engineering
nov., 2019 - déc., 2023
4 ans, 1 mois
Data scientist and machine learning engineer
janv., 2023 - déc., 2023
11 mois
I worked on fatal heat in the industry where I had to process simultaneously time-series and categorical data to find the optimal heat-transfer solution using reinforcement learning. I used python and tensorflow for data processing and machine learning.
Data scientist and AI engineer
nov., 2019 - déc., 2023
4 ans, 1 mois
I worked on the detection of pressure ulcers based on time-series. In this project, I used gradient-boosted random forest and LSTMs to predict the probabilities of pressure ulcers. For my algorithm to perform best, I had to engineer new features based on relationships between pressure ulcers and the input data. I used python for data processing and machine learning.
nov., 2019 - déc., 2023
4 ans, 1 mois
Formation
Université d'Angers
2016 - 2019
3 ans
Doctorate in signal processing
Drapeau de
France
2016 - 2019
3 ans
Publications
Early Detection of Pressure Ulcers: Considering the Reperfusion
Innovation and Research in BioMedical engineering
We compared different algorithms for the early detection of pressure ulcers and showed the need to take the measurement variation in time for a better detection. We showed that taking the evolution of pressure instead of only instantaneous measurement can improve the early detection of pressure ulcer.
Evaluation of 3D/2D Imaging and Image Processing Techniques for the Monitoring of Seed Imbibition
Journal of imaging
Seed imbibition is an important process in plant biology by which a dry seed may turn into a developing organism. Monitoring the seed imbibition with non-invasive imaging techniques is therefore an important task. We described four different imaging techniques that address this task either in 3D or in 2D. Complete image analysis pipelines are then proposed to extract dynamic information on the imbibition process from such monitoring experiments.
Stochastic antiresonance in qubit phase estimation with quantum thermal noise
Elsevier
We consider a quantum information processing task consisting in estimating the phase of a qubit. Estimation is analyzed in the presence of decoherence represented by a quantum thermal noise at arbitrary temperature. Regimes are found where higher noise temperatures turn more favorable to estimation. Such behaviors are related to stochastic resonance or antiresonance effects, where noise reveals beneficial to information processing.
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