The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered. Finally, several other Deep learning methods will be covered.
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Habilidades en redes de IBMAcerca de este Curso
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Certificado para compartir
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100 % en línea
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Nivel intermedio
Aprox. 31 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Aprox. 31 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
Habilidades en redes de IBM
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Programa - Qué aprenderás en este curso
5 horas para completar
Tensor and Datasets
5 horas para completar
6 videos (Total 44 minutos)
2 horas para completar
Linear Regression
2 horas para completar
7 videos (Total 35 minutos)
3 horas para completar
Linear Regression PyTorch Way
3 horas para completar
5 videos (Total 21 minutos)
2 horas para completar
Multiple Input Output Linear Regression
2 horas para completar
4 videos (Total 18 minutos)
2 horas para completar
Logistic Regression for Classification
2 horas para completar
4 videos (Total 31 minutos)
2 horas para completar
Softmax Rergresstion
2 horas para completar
3 videos (Total 18 minutos)
3 horas para completar
Shallow Neural Networks
3 horas para completar
6 videos (Total 33 minutos)
Reseñas
- 5 stars63,86 %
- 4 stars23,19 %
- 3 stars5,71 %
- 2 stars4,11 %
- 1 star3,10 %
Principales reseñas sobre DEEP NEURAL NETWORKS WITH PYTORCH
por D9 de jun. de 2022
The explanation is simple and understandable. They explained deep neural networks so beautifully with PyTorch. Thank you very much for this course IBM.
por DD12 de jul. de 2020
Excellent Course. I love the way the course was presented. There were a lot of practical and visual examples explaining each module. It is highly recommended!
por GC3 de ago. de 2020
Great introduction to deep learning with pytorch. It would help if the notebooks in the labs take shorter to run so that the students can experiment with the code and the models.
por UJ2 de nov. de 2020
Amazing course for a beginner in Deep Learning & Pytorch.
I gave 4 stars as I expected it to be more pytorch heavy.
Overall, a really good crafted course.
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