Overview of Deep Learning concepts. Understand what are the Deep Learning Models, Platforms, Libraries and how they work
What you’ll learn
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Introduction to Deep Learning
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Understand what are Neural Networks
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Deep Learning market, scope, opportunities
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Deep Learning Models
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Restricted Boltzmann Machines, Deep Belief Network, Convolutional Network, Recurrent Network
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Autoencoders, Recursive Neural Tensor Network, Generative Adversarial Networks
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Deep Learning Platforms & Libraries
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Deep Net Platform, H2O ai, Dato GraphLab
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Theano, Caffe, TensorFlow, Keras
Description
Deep Learning Foundation – Syllabus
Module 1 – Introduction to Deep Learning
- Deep Learning: The Series Introduction
- What is a Neural Network
- Three reasons to go Deep
- Your choice of Deep Net
- Deep Learning Market
Module 2 – Deep Learning Models
- Restricted Boltzmann Machines
- Deep Belief Network
- Convolutional Network
- Recurrent Network
Module 3 – Additional Deep Learning Models
- Autoencoders
- Recursive Neural Tensor Network
- Generative Adversarial Networks
Module 4 – Deep Learning Platforms & Libraries
- What is a Deep Net Platform
- H2O ai
- Dato GraphLab
- What is a Deep Learning Library
- Theano
- Caffe
- TensorFlow
- Keras
Who this course is for:
- Deep Learning Scientists
- Machine Learning Engineers
- Data Scientists & Senior Data Scientists
- Newbies and Beginners aspiring for a career in Deep Learning and Machine Learning
- AI Researchers – Complex Algorithms, Deep Learning Models
- Deep Learning Researchers / Development Engineers
- Data Consultants & Analysts
- Computer Vision Engineers
- Data Science & Artificial Intelligence Managers
- Individuals interested in learning the fundamentals of Deep Learning
- Deep Learning Interns
- Software Engineers and Advanced Programmers
- Optimization Analysts
- Technology Consultants
- Big Data Scientists
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