This comprehensive Deep Learning program will equip you with advanced skills in TensorFlow, Keras, Recurrent Neural Networks (RNNs), and Neural Networks. You’ll learn to implement cutting-edge AI models and frameworks to tackle real-world challenges and drive impactful innovations.
Deep Learning Frameworks and Neural Networks Simplified
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Deep Learning Frameworks and Neural Networks Simplified
Instructor: Simplilearn Instructor
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Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
5 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
Master TensorFlow and Keras for model building and object detection
Apply RNNs and LSTM networks for sequential data tasks
Explore feedforward, convolutional, and recurrent neural networks
Build and deploy AI models to solve real-world challenges
Skills you'll gain
Details to know
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Recently updated!
January 2025
Assessments
1 assignment
Taught in English
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There are 2 modules in this course
This comprehensive Deep Learning program will equip you with advanced skills in TensorFlow, Keras, Recurrent Neural Networks (RNNs), and Neural Networks. You’ll learn to implement cutting-edge AI models and frameworks to tackle real-world challenges and drive impactful innovations. Guided by experts, you’ll gain the technical expertise and practical knowledge needed to excel in the fast-evolving field of deep learning.
What's included
26 videos3 readings
This comprehensive Deep Learning program will equip you with advanced skills in TensorFlow, Keras, Recurrent Neural Networks (RNNs), and Neural Networks. You’ll learn to implement cutting-edge AI models and frameworks to tackle real-world challenges and drive impactful innovations. Guided by experts, you’ll gain the technical expertise and practical knowledge needed to excel in the fast-evolving field of deep learning.
What's included
1 assignment
Instructor
Offered by
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Frequently asked questions
TensorFlow and PyTorch are among the most popular frameworks for deep learning, offering robust libraries, community support, and flexibility for building and training neural networks.
Start with the basics of AI and machine learning, then progress to neural networks and frameworks like TensorFlow or PyTorch. Hands-on practice with projects and online courses can accelerate learning.
The three types of learning are supervised learning (using labeled data), unsupervised learning (working with unlabeled data), and reinforcement learning (training through rewards and penalties).