The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering hidden structures within this type of data. In this course you’ll use TensorFlow library to apply deep learning to different data types in order to solve real world problems.
Este curso forma parte de Certificado profesional de IBM AI Engineering
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Curso 5 de 6 en
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Nivel intermedio
Aprox. 13 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Instructores
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 5 de 6 en
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 13 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
ofrecido por
IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Programa - Qué aprenderás en este curso
5 horas para completar
Introduction
In this module, you will learn about TensorFlow, and use it to create Linear and Logistic Regression models.
5 horas para completar
5 videos (Total 28 minutos), 1 lectura, 5 cuestionarios
5 videos
Welcome2m
Introduction to TensorFlow7m
TensorFlow 2.x and Eager Execution4m
Introduction to Deep Learning2m
Deep Neural Networks11m
1 lectura
Syllabus10m
1 ejercicio de práctica
Deep Neural Networks and TensorFlow30m
2 horas para completar
Supervised Learning Models
In this module, you will learn about about Convolutional Neural Networks, and the building blocks of a convolutional neural network, such as convolution and feature learning. You will also learn about the popular MNIST database. Finally, you will learn how to build a Multi-layer perceptron and convolutional neural networks in Python and using TensorFlow.
2 horas para completar
3 videos (Total 22 minutos)
3 videos
Convolutional Neural Networks (CNNs) for Classification4m
Convolutional Neural Networks (CNNs) Architecture13m
1 ejercicio de práctica
Convolutional Neural Networks30m
3 horas para completar
Supervised Learning Models (Cont'd)
In this module, you will learn about the recurrent neural network model, and special type of a recurrent neural network, which is the Long Short-Term Memory model. Also, you will learn about the Recursive Neural Tensor Network theory, and finally, you will apply recurrent neural networks to language modelling.
3 horas para completar
4 videos (Total 22 minutos)
4 videos
Recurrent Neural Networks (RNNs)5m
The Long Short Term Memory (LSTM) Model5m
Language Modelling7m
1 ejercicio de práctica
Recurrent Neural Networks30m
2 horas para completar
Unsupervised Deep Learning Models
In this module, you will learn about the applications of unsupervised learning. You will learn about Restricted Boltzmann Machines (RBMs), and how to train an RBM. Finally, you will apply Restricted Boltzmann Machines to build a recommendation system.
2 horas para completar
2 videos (Total 10 minutos)
1 ejercicio de práctica
Restricted Boltzmann Machines30m
Reseñas
Principales reseñas sobre BUILDING DEEP LEARNING MODELS WITH TENSORFLOW
por RR25 de jul. de 2020
Nice course to introduce you to more advanced neural network algorithms, I wish the evaluations were more challenging and based on practical exercises... there is no final assignment either.
por HJ17 de may. de 2020
It would have been nice if the video tutorials would explain the code section as well, and if there would have been some in-depth teaching of the code part. But this course did benefit.
por RC14 de may. de 2020
Good an simple videos to understand the concept. The notebooks are very detailed and give a second layer of knowledge with practical example
por ZR2 de jul. de 2020
Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!
Acerca de Certificado profesional de IBM AI Engineering
Artificial intelligence (AI) is revolutionizing entire industries, changing the way companies across sectors leverage data to make decisions. To stay competitive, organizations need qualified AI engineers who use cutting-edge methods like machine learning algorithms and deep learning neural networks to provide data driven actionable intelligence for their businesses. This 6-course Professional Certificate is designed to equip you with the tools you need to succeed in your career as an AI or ML engineer.
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