Ce cours vous apprendra 脿 cr茅er des r茅seaux neuronaux convolutifs et 脿 les appliquer aux donn茅es d'image. Gr芒ce 脿 l'apprentissage en profondeur, la vision par ordinateur fonctionne beaucoup mieux qu'il y a seulement deux ans, ce qui permet de nombreuses applications passionnantes allant de la conduite autonome en toute s茅curit茅, 脿 la reconnaissance faciale pr茅cise, 脿 la lecture automatique des images radiologiques.
R茅seaux neuronaux convolutifs
Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
4 assignments
Taught in French
See how employees at top companies are mastering in-demand skills
There are 4 modules in this course
Apprendre 脿 mettre en 艙uvre les couches de base des CNN (mise en commun, convolutions) et 脿 les empiler correctement dans un r茅seau profond pour r茅soudre les probl猫mes de classification d'images multi-classes.
What's included
12 videos4 readings1 assignment2 programming assignments2 ungraded labs
D茅couvrir les astuces pratiques et les m茅thodes utilis茅es dans les CNN profonds directement 脿 partir des articles de recherche.
What's included
11 videos1 reading1 assignment1 programming assignment2 ungraded labs
Apprendre 脿 appliquer vos connaissances des CNN 脿 l'un des domaines les plus difficiles mais les plus sensibles de la vision par ordinateur : D茅tection d鈥檕bjets.
What's included
10 videos2 readings1 assignment1 programming assignment1 ungraded lab
D茅couvrez comment les CNN peuvent 锚tre appliqu茅s 脿 plusieurs domaines, y compris la g茅n茅ration d'art et la reconnaissance faciale. Mettez en 艙uvre votre propre algorithme pour g茅n茅rer de l'art et reconna卯tre les visages !
What's included
11 videos3 readings1 assignment2 programming assignments2 ungraded labs
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Frequently asked questions
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