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This video on What is Deep Learning provides a simple and fun introduction to its concepts. We learn where Deep Learning is implemented and discuss how it differs from machine learning and artificial intelligence. We'll also look at what neural networks are and how they are trained to recognize handwritten numbers. We take a closer look at some popular applications of Deep Learning. So, let’s dive into the world of Deep Learning with this video.

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Watch more videos on Deep Learning: https://www.youtube.com/watch?vFbxTVRfQFuI&listPLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip

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Why Deep Learning?
It is one of the most popular software platforms used for Deep Learning and contains powerful tools to help you create and implement artificial neural networks.
Advances in deep learning can be seen in smartphone applications, creating efficiencies in the power grid, driving advances in healthcare, improving agricultural yields, and helping us find solutions to climate change. According to payscale.com, the median salary for engineers with deep learning skills exceeds 120,000 per year.

You can gain in-depth knowledge of Deep Learning by following our Deep Learning certification training. With Simplilearn's Deep Learning course, you'll prepare for a career as a Deep Learning engineer by mastering concepts and techniques including supervised and unsupervised learning, mathematics and heuristics, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Understand the concepts of TensorFlow, its main functions, operations and execution pipeline
2. Implement Deep Learning algorithms, understand neural networks, and navigate layers of data abstraction that will allow you to understand data like never before.
3. Master and understand advanced topics such as convolutional neural networks, recurrent neural networks, deep network training and high-level interfaces
4. and more

️About AI and Machine Learning Bootcamp
The AI and Machine Learning Bootcamp provides Caltech CTME's academic prowess to help accelerate your career in data science. Statistics, Python, machine learning, deep learning, natural language processing, and supervised learning are all included in this AI and machine learning bootcamp.

Main characteristics
– Earn up to 22 CEUs from Caltech CTME
– Get a bootcamp certificate from Caltech CTME
– Membership in the Caltech CTME Circle
– Online invitation by the Caltech CTME program director
– Industry relevant capstone projects in 3 areas
– 25 hands-on projects across all industry sectors with integrated labs

Required Skills
– Statistics
-Python
– Supervised teaching
– Unsupervised learning
– Recommendation systems
– NLP
– Neural networks
-GAN
– Deep learning

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