Comment l'IA démultiplie les fonctions cognitives ? - French Tech ...
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
« Meetup Data Science »
Mercredi 4 mars 2020
Comment l’IA démultiplie les fonctions cognitives ?
A variant of machine learning engineer is called
Deep Learning engineer. This role requires deep
learning knowledge in addition to the skills profile
Jean-Marie PRIGENT (Modeling, Deployment, Data Engineering). It
focuses on applications, usually powered by deep
ML Engineer learning, such as speech recognition, natural
language processing, and computer vision. Hence, it
Altran Brest requires skills specific to deep learning projects such
as understanding and using various neural network
architectures such as fully connected networks,
CNNs, and RNNs.
P as Passionately curious... Big Data and DL but not only… Drones, FPV, CV, Maker, 3D Printer, Electronics, DonkeyCar, Edge, ... linkedin.com/in/jmprigent
Machine Learning Ecosystem
Machine Learning Languages: Data Processing:
- Python / R / (C++) - BIG Data framework
(Cloudera/HDP/Oozie/Pig/Spark/
General Machine Learning Frameworks Scala )
- Numpy - Apache Airflow, NIFI
- Scikit-Learn
- NLTK, Spacy Hardware Training:
- CPU, GPU, TPU, Cloud
Data Analysis and Visualisation tools - Distrubuted (Spark, Kubeflow)
- Pandas - Federated Learning (WO
- Matplotlib centralized server)
- Jupyter Notebook
Inference
ML frameworks for neural networks - Desktop, server …
modelling - Mobile
- Tensorflow / Tensorboard - Edge device (VPU: Intel NCS2,
- Keras GPU: Jetson Nano & TPU: Coral
- Pytorch dev board, Coral stick)
- (Caffe2, mxnet)
What is Deep Learning ?
Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning.
Learning can be supervised, semi-supervised or unsupervised.
Deep learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural
networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition,
social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game
programs, where they have produced results comparable to and in some cases surpassing human expert performance
Deep Learning : “a
technique for
implementing Machine
Learning”
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent
Le Deep Learning dans l’Univers de l’IA...
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent
Le Deep Learning dans l’Univers de l’IA...
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent
Some dates in the field of IA
1980 – Kunihiko Fukushima built the ‘neocognitron’, the precursor of modern Convolutional Neural Networks.
2001 – Two researchers at MIT introduced the first face detection framework (Viola-Jones) that works in real-time.
2009 – Google started testing robot cars on roads.
2010 – Google released Goggles, an image recognition app for searches based on pictures taken by mobile devices.
2010 – To help tag photos, Facebook began using facial recognition.
2011 – Facial recognition was used to help confirm the identity of Osama bin Laden after he is killed in a US raid.
2012 – Google Brain’s neural network recognized pictures of cats using a deep learning algorithm.
2015 – Google launched open-source Machine learning-system TensorFlow.
2016 – Google DeepMind’s AlphaGo algorithm beat the world Go champion.
2017 – Apple released the iPhone X in 2017, advertising face recognition as one of its primary new features.
2018 – Alibaba’s AI model scored better than humans in a Stanford University reading and comprehension test.
2018 – Amazon sold its real time face recognition system Rekognition to police departments.
2019 – The Indian government announced a facial recognition plan allowing police officers to search images through mobile app.
2019 – The US added four of China’s leading AI start-ups to a trade blacklist.
2019 – The UK High Court ruled that the use of automatic facial recognition technology to search for people in crowds is lawful.
2025 – By this time, regulation in FR will significantly diverge between China and US/Europe.
2030 – At least 60% of countries globally will be using AI surveillance technology (it is currently 43% according to CEIP).
This is an edited extract from the Computer Vision – Thematic Research report produced by GlobalData Thematic Research.
https://www.verdict.co.uk/computer-vision-timeline/
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent
Apprentissage supervisé
“L’objectif de l’apprentissage supervisé est d’apprendre une fonction
qui, à partir d’un échantillon de données et des résultats souhaités, se
rapproche le mieux de la relation entre entrée et sortie observable
dans les données.”
-> Y = f (X)
L’apprentissage supervisé est généralement effectué dans le contexte
de la classification et de la régression.
Classification: Un problème de classification survient lorsque la
variable de sortie est une catégorie, telle que «rouge», «bleu» ou
«maladie» et «pas de maladie».
Régression: Un problème de régression se pose lorsque la variable
de sortie est une valeur réelle, telle que «dollars» ou «poids».
source: https://le-datascientist.fr/apprentissage-supervise-vs-non-supervise
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent
Apprentissage non supervisé
“L’apprentissage non supervisé (Unsupervised Learning) consiste à
ne disposer que de données d’entrée (X) et pas de variables de sortie
correspondantes.
L’objectif est de modéliser la structure ou la distribution sous-jacente
dans les données afin d’en apprendre davantage sur les données.
On l’appelle apprentissage non supervisé car, contrairement à
l’apprentissage supervisé, il n’y a pas de réponse correcte ni
d’enseignant. Les algorithmes sont laissés à leurs propres
mécanismes pour découvrir et présenter la structure intéressante des
données.”
Regroupement ou clustering: l’objectif est de séparer les groupes
ayant des traits similaires et de les assigner en grappes.
Association: consiste à découvrir des relations intéressantes entre
des variables dans de grandes bases de données. Par exemple, les
personnes qui achètent une nouvelle maison ont aussi tendance à
acheter de nouveaux meubles
source: https://le-datascientist.fr/apprentissage-supervise-vs-non-supervise
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent
Apprentissage semi supervisé
“Les problèmes pour lesquels vous avez une grande quantité de
données d’entrée (X) et que seules certaines données sont étiquetées
(Y) sont appelés problèmes d’apprentissage semi-supervisés. Par
conséquent, ces problèmes se situent entre l’apprentissage supervisé
et l’apprentissage non supervisé”
Le Deep Learning rentre dans la catégorie
“supervisé” pour la majorité des cas et plus
récemment semi supervisé avec les GAN.
Le (Deep) Reinforcement Learning rentre dans la
categorie non supervisé
source: https://le-datascientist.fr/apprentissage-supervise-vs-non-supervise
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentA Visual and Interactive Guide to the Basics of Neural
Networks...in a nutshell
source: jay Alammar Blog
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentA Visual and Interactive Guide to the Basics of Neural
Networks...in a nutshell
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentA Visual and Interactive Guide to the Basics of Neural
Networks...in a nutshell
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentA Visual and Interactive Guide to the Basics of Neural
Networks...in a nutshell
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentWhat convolution neural network see...
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentSome vocab in Computer Vision tasks
4 differents tasks in CV:
- image classification
- object detection
- semantic segmentation
- instance segmentation
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentImaging Applications
Deep Learning has applications in all sectors of
activity. It is a major issue for the industrial and
scientific sectors and the safety of goods and
people.
Among these uses are in particular :
- Image recognition (classification, localization
and segmentation),
- Description of scenes,
- Facial recognition (security),
- Optical Character Recognition (OCR),
- Content-Based Images Retrieval (CBIR)
- Medical Imaging (biology, histology, radiology),
- Synthetic image generation (GAN),
- Emotion detection,
- Detection of age and gender,
…
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentNLP-NLU Applications
NLP iis becoming more democratic, previously
reserved for researchers.
The advent of personal assistants (Siri, Alexa,
Google Home) and its high level of adoption proves
the maturity of this technology.
Studies prove that using a text transcriber is 3 times
faster than writing the text.
Among the cases of use are the following:
- Chatbots
- Spam detection / Spam filter avoidance
- Sentiment analysis (consumer opinions, customer
opinions)
- E-reputation
- Automated translation
- Subtitling of video sequences (Speech-to-Text)
- Voice User Interface (VUI) (Siri, Alexa, Ok Google)
…
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentGet datas … and Training Neural Network
tensorboard UI
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentTraining sample on Fashion-MNIST under Colab
Fashion Mnist
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent3/ Inference :
a/ Desktop | server
b/ Mobile
c/ Edge device (low power 2-15w)
d/ ARMs (only some basic features like sound triggering)
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent… But the REAL ML Pipeline is ...
- Collect and prepare data
- Developing a model
- Training an ML model on the data : “Only 5-15% of
Training the model the ML pipeline
Evaluate the accuracy of the model
Setting the hyperparameters is ML/DL“ !
- Deploy the driven model Andrew Ng
- Send prediction queries to the model :
Online prediction
Batch Prediction
- Monitor predictions continuously
- Manage models and versions
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentA as ART
1/ Autodraw
Autodraw: find object shape
Autodraw
2/ Style Transfer
Artiste Fred: Toile
Les toiles de Fred
file:///Users/jmp/Desktop/prez_bia/1_style_transfer/Core1_Introduc
tions/neural_style_fred.html
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentRT as Real time counting
YOLO V3
It took 1.958 seconds to detect the objects in the image.
Number of Objects Detected: 20
Objects Found and Confidence Level:
1. person: 1.000000
2. person: 1.000000
3. person: 1.000000
4. person: 1.000000
5. person: 1.000000
6. person: 1.000000
7. person: 1.000000
8. person: 1.000000
9. person: 1.000000
10. person: 1.000000
11. person: 1.000000
12. boat: 0.998270
13. person: 0.999997
14. person: 0.999981
15. person: 0.999952
16. person: 0.999981
17. person: 0.999994
18. person: 1.000000
19. person: 1.000000
20. person: 0.999979
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentDetection en temps reel
YOLO V3 by Joseph Redmon
> Demo mobile Yolo
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentTeachable machine by Google
https://experiments.withgoogle.com/teachable-machine
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentP as Pose Estimation
Demo pose estimation inference directly in
browser
35FPS with tensorflow js
Pose estimation with TensorFlow.js
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentS as Sons: create sound with image only
Imaginary soundscape by Google:
http://www.imaginarysoundscape.net/#/upload
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentD as Driver Security (outside)
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentM as Mobility
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentA as Attention : Driver Security (inside)
Drowiness and Distraction detector
source: https://github.com/incluit/OpenVino-Driver-Behaviour
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentPT as Pedestrian tracking
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentPT as Pedestrian counter
Single Shot Detector (SSD)
with Opencv DNN
source: https://www.pyimagesearch.com/2018/08/13/opencv-people-counter/
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentT comme Tracking
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentImage captioning: CV and NLP...
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentH as high accuracy and celerity
Detectron2 by Facebook
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentD as Driver assist
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentS as Security: weapons detection
Collection of handgun images, procured and
RetinaNet, a deep learning-based object published by Olmos et al. in their 2018
detection architecture that seeks to publication, “Automatic handgun detection
combine both the speed of one-stage alarm in videos using deep learning”
detectors (ex., YOLO and SSD) with the
accuracy of slower two-stage detectors
(ex., Faster R-CNN)
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentCD as Cancer Identification
Mask R-cnn
Train a Mask R-CNN instance segmentation
network to automatically detect skin lesions, a
first step in cancer identification.
The ISIC Skin Lesion Dataset
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentP Pills classification
Train a Mask R-CNN instance
segmentation network to automatically
detect pills.
Mistakes surrounding prescription
medication can and do happen,
resulting in billions of euros in insurance
claims, hospital bills, and of course, the
incalculable value of a human.
In France, with D.I.N, clinics and
hospital needs CV assisted Robot with The ISIC Skin Lesion Dataset
DL features -> Brest CHU
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentF as Fish Classifier
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentF as Fraud Detection
Training set New Data
Training Inference
source: Manning MEAP: “Deep Learning with Structured Data”
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentS comme Summarization
- Bert language model
- Bert Extractiver summrization
- Neural coreference : coreference is the fact that two or more expressions in a text – like pronouns or nouns – link to the same person or thing
Capgemini et Altran Technologies s'unissent. Les deux géants ont conclu un accord de négociations exclusives en vue de l’acquisition par Capgemini d’Altran dans le cadre d’une OPA amicale à 14 euros par action Altran,
payables en numéraire. Le montant total de la transaction s’élèvera à 3,6 milliards d’euros, avant prise en compte de la dette financière nette d’environ 1,4 milliard d’euros. "Ce rapprochement aura un impact
immédiatement relutif, évalué à plus de 15% sur le résultat normalisé par action avant mise en œuvre des synergies ", expliquent les deux groupes, qui ajoutent qu'en "2023, après prise en compte des synergies, la
relution devrait dépasser 25%".
L'accord a été approuvé à l'unanimité par les conseils d'administration de Capgemini et d'Altran. Par ailleurs, Capgemini a d'ores et déjà signé un accord définitif pour l'acquisition d'un bloc de 11% du capital d'Altran
auprès d'actionnaires autour d'Apax Partners. L'opération vise la création d'un groupe de 17 milliards d'euros de chiffre d'affaires et de plus de 250 000 collaborateurs par le rapprochement d'un spécialiste du conseil et
des services informatiques et d'un spécialiste des services d'ingénierie et de R&D. La finalisation de ce rapprochement est envisagée d'ici la fin de l'exercice 2019.
Capgemini indique avoir sécurisé un financement relais de 5,4 milliards d'euros, comprenant l'achat des titres et le rachat de la dette brute de 1,8 milliard d'euros. "Ce rapprochement, cette OPA amicale, n'est pas un
changement de stratégie pour nous. On l'a appuyé avec beaucoup d'enthousiasme et de passion. Cela crée un superchampion", s'est réjoui le PDG d'Altran Dominique Cerutti lors d'une conférence téléphonique, rapporte
l'AFP. "L'expertise de Capgemini et celle d'Altran sont parfaitement complémentaires et proposeront une combinaison unique sur le marché. Les entreprises sont très friandes d'innovation et nous allons accélérer grâce à
notre nouvelle taille critique", a renchéri le patron de Capgemini Paul Hermelin.
Cette OPA entre le champion des entreprises de services numériques et celui du conseil en technologies devrait bouleverser le paysage de la "tech" française. Paul Hermelin a exclu que Capgemini ait besoin de céder des
actifs pour des raisons de concurrence après cet accord. "On n'est pas sur des parts de marchés qui provoquent ce genre de demandes", a-t-il indiqué, rapporte l'AFP.
Grâce à l'opération, les deux groupes visent des synergies de coûts et de modèles opérationnels estimés "entre 70 et 100 millions d'euros avant impôts en année pleine" et un chiffre d'affaires annuel additionnel compris
entre "200 et 350 millions d'euros" d'ici trois ans.
{
"summary": "Capgemini et Altran Technologies s'unissent. L'opération vise la création d'un groupe de 17 milliards d'euros de chiffre d'affaires et de plus de 250 000
collaborateurs par le rapprochement d'un spécialiste du conseil et des services informatiques et d'un spécialiste des services d'ingénierie et de R&D. La finalisation de ce
rapprochement est envisagée d'ici la fin de l'exercice 2019. Grâce à l'opération, les deux groupes visent des synergies de coûts et de modèles opérationnels estimés \"entre 70 et
100 millions d'euros avant impôts en année pleine\" et un chiffre d'affaires annuel additionnel compris entre \"200 et 350 millions d'euros\" d'ici trois ans."
}
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentLaunched by Ifremer in March 2017, the citizen
science project “Espion des Grands Fonds”
Help our local biologists by playing
deepseaspy! Need HELP
www.deepseaspy.com
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentLaunched by Ifremer in March 2017, the citizen
science project “Espion des Grands Fonds”
Help our local biologists by playing
deepseaspy. www.deepseaspy.com
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentMussels Annotations
Ifremer's Deep Environment Laboratory studies the evolution of mussel beds using
submerged cameras that take one photo per hour over ten years to measure their evolution.
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentMussels Segmentation
inference: automatic detection of Mussels with
Mask R-cnn
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentD as DeepFake
“Deepfakes are fake videos or
audio recordings that look and
sound just like the real thing”
-> beware of the deepfake !!!
live deepfake generation with webcam feed
extract facial landmarks
source video
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentD as Dance
“Everybody Dance Now” (2019-08-29)
- Pose estimation
- Pose normalisation
- Mapping normalized pose stick figures
to Target subject
source: https://arxiv.org/pdf/1808.07371.pdf
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentD as DonkeyCar
➔ DonkeyCar is a high level self driving library written in Python. It
was developed with a focus on enabling fast experimentation and
easy contribution. It is has been called the Hello World of
autonomous vehicles.
➔ It is open source with an active community and support channel.
➔ Active users around the world include tinkerers, educators,
educational institutions and companies.
➔ Main site: www.donkeycar.com
★ Open Source, Python ➔ Github: https://github.com/autorope/donkeycar
★ OpenCV, TensorFlow, Keras, CNN, Deep Learning ➔ Community: Discord or Slack
★ Raspberry Pi, Nvidia Jetson, GPU, Google Coral TPU
★ Behavioral Cloning, Data Augmentation
★ Transfer Learning, Reinforcement Learning
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentD as DonkeyCar
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentQ as Questions ....
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentExtra Content
Machine learning for creators but not only
https://runwayml.com/
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigentsource: source: artificial-intelligence/glossary Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent
P as Papers … a lot ...
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentM comme Mobility https://selfdrivingcars.mit.edu/deeptraffic/
Meetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie PrigentMeetup Data Sciences - Brest is IA - 2020-03-04 - Jean-Marie Prigent
You can also read
