Packt
Deep Learning: Recurrent Neural Networks with Python Specialization
Packt

Deep Learning: Recurrent Neural Networks with Python Specialization

Build Recurrent Neural Networks with Python. One-stop shop for understanding and implementing recurrent neural networks with Python.

Packt

Instructor: Packt

Included with Coursera Plus

Get in-depth knowledge of a subject
Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Identify the key components of deep neural networks, and train real-world datasets using different RNN architectures

  • Design and implement text classification tasks using RNNs and TensorFlow

  • Differentiate between RNNs, LSTM, and GRUs through hands-on exercises

Details to know

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Taught in English
Recently updated!

September 2024

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Specialization - 3 course series

Introduction to RNN and DNN

Course 16 hours

What you'll learn

  • Utilize PyTorch to build and optimize AI models.

  • Examine the effectiveness of gradient descent and hyperparameter tuning in model optimization.

  • Develop and apply RNN models for complex tasks such as speech recognition and machine translation.

Skills you'll gain

Category: Recurrent Neural Network
Category: Deep Learning
Category: AI Applications
Category: Machine Learning
Category: Deep Neural Networks
Category: Data Science
Category: Recurrent Neural Networks

What you'll learn

  • Identify different RNN architectures, including fixed-length and infinite memory models.

  • Examine the effectiveness of gradient descent and backpropagation through time in training RNN models.

  • Develop and apply RNN models for advanced tasks such as sentiment analysis and language modeling.

Skills you'll gain

Category: Machine Learning
Category: PyTorch (Machine Learning Library)
Category: AI Sentiment Classification
Category: Sentiment Analysis
Category: Recurrent Neural Networks

What you'll learn

  • Identify key components and functionalities of GRUs, LSTMs, and attention mechanisms.

  • Utilize TensorFlow to build, train, and optimize RNN models.

  • Develop and implement advanced RNN models to solve complex problems.

Skills you'll gain

Category: Vanishing Gradient
Category: GRU and LSTM Models
Category: Text Generation AI
Category: TensorFlow
Category: Recurrent Neural Networks

Instructor

Packt
Packt
196 Courses2,786 learners

Offered by

Packt

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