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$30 USD / time
Flag for MOROCCO
fès, morocco
$30 USD / time
Det er i øjeblikket 1:22 PM her
Tilmeldt februar 1, 2019
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Mouad A.

@mouadablad

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$30 USD / time
Flag for MOROCCO
fès, morocco
$30 USD / time
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Genansættelsesrate

IBM Certified Big Data Engineer

I am a Data Scientist with strong problem solving skills. I Possess extensive skills and expertise as a Python Developer, Data Scientist, and Machine learning Engineer. I have worked on several projects in these niche and you can message me for samples. I am all about DATA, so you can trust me to give you the best services.

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Uddannelse

Master of Science : Big Data Analytics and Smart Systems

Université Sidi Mohammed Ben Abdellah-Fès, Morocco 2018 - 2020
(2 år)

Bachelor of Science : Mathematics and Computer Science

Université Sidi Mohammed Ben Abdellah-Fès, Morocco 2014 - 2018
(4 år)

Kvalifikationer

IBM AI Engineering Professional Certificate

IBM
2020
This badge earner has demonstrated proficiency in Machine Learning (ML) and Deep Learning (DL). The earner understands various ML techniques such as regression, classification, clustering & recommender systems and is able to scale ML on Big Data using Apache Spark. The earner is able to build, test & deploy DL models using libraries such as Keras, PyTorch & Tensorflow. The earner has completed several ML & DL projects and is now armed with skills for starting a career in AI Engineering.

Computer Vision V2

IBM
2020
Through self-paced learning, this badge earner has completed the skill learning journey on topics such as defining what Computer Vision is, Computer Vision tools and services, Image representation, Computer Vision pipeline, Vision services on IBM Watson, and create a service and train it to build your own custom visual recognition model.

Big Data Engineer - Mastery Award 2018

IBM
2020
The badge earner has a proven expertise to use Big Data methodologies to collect & analyze large amounts of data from different sources, using IBM Watson Studio and Open Source Tools. The badge earner has demonstrated advanced proficiency on topics such as Apache Hadoop, Ambari, Spark, Big SQL, HDFS, YARN, MapReduce, ZooKeeper, Knox, Sqoop, and HBase.

Publikationer

Uncertainty Quantification in Deep Learning Context: Application to Insurance

IEEE
In this work, we proposed a solution to detect automobile insurance fraud with quantified uncertainty, our model uses two methods to quantify uncertainty. The first one is called Monte Carlo Dropout method, which is considered as an approximate Bayesian inference in deep Gaussian processes. The second is named Deep Ensembles method. These two methods mitigate the problem of representing uncertainty in deep learning without sacrificing either computational complexity or test accuracy.

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