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IBM: Deep Learning Fundamentals with Keras

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New to deep learning? Start with this course, that will not only introduce you to the field of deep learning but give you the opportunity to build your first deep learning model using thepopular Keras library.

Deep Learning Fundamentals with Keras
5 semanas
2–4 horas por semana
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Comienza el 21 nov
Termina el 30 dic

Sobre este curso

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Please Note: Learners who successfully complete this IBM course can earn a skill badge —a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

Looking to kickstart a career in deep learning? Look no further. This course will introduce you to the field of deep learning and teach you the fundamentals. You will learn about some of the exciting applications of deep learning, the basics fo neural networks, different deep learning models, and how to build your first deep learning model using the easy yet powerful library Keras.

This course will presentsimplified explanations to some oftoday's hottest topics in data science, including:

  • What is deep learning?
  • How do neural networks learn and what are activation functions?
  • What are deep learning libraries and how do they compare to one another?
  • What are supervised and unsupervised deep learning models?
  • How to use Keras to build, train, and test deep learning models?

The demand fordeep learning skills-- and the job salaries of deep learning practitioners -- arecontinuing to grow, as AI becomes more pervasive in our societies. This course will help you build the knowledge you need to future-proofyour career.

Premios

Deep Learning Essentials with Keras

De un vistazo

  • Language English
  • Video Transcripts اَلْعَرَبِيَّةُ, Deutsch, English, Español, Français, हिन्दी, Bahasa Indonesia, Português, Kiswahili, తెలుగు, Türkçe, 中文
  • Associated programs
  • Associated skillsArtificial Neural Networks, Data Science, Artificial Intelligence, Deep Learning, Keras (Neural Network Library)

Lo que aprenderás

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  • You will learn about exciting applications of deep learning and why it is really rewarding to learn how to leverage deep learning skills.
  • You will learn about neural networks and how theylearn and update their weights and biases.
  • You will learn about thevanishing gradient problem.
  • You will learn about building a regression model using the Keras library.
  • You will learn about building a classification model using the Keras library.
  • You will learn about supervised deep learning models, such as convolutional neural networks and recurrent neural networks, and how to build a convolutional neural network using the Keras library.
  • You will learn about unsupervised learning models such as autoencoders.

Plan de estudios

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Module1 - Introduction to Deep Learning
- Introduction to Deep Learning
- Biological Neural Networks
- Artificial Neural Networks - Forward Propagation

Module2 -Artificial Neural Networks
- Gradient Descent
- Backpropagation
- Vanishing Gradient
- Activation Functions

Module3 - Deep Learning Libraries
- Introduction to Deep Learning Libraries
- Regression Models with Keras
- Classification Models with Keras

Module4 -Deep Learning Models
- Shallow and Deep Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Autoencoders

¿Quién puede hacer este curso?

Lamentablemente, las personas residentes en uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.

Este curso es parte del programa Deep Learning Professional Certificate

Más información 
Instrucción por expertos
6 cursos de capacitación
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7 meses
2 - 4 horas semanales

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