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Deep Learning | A Step Closer To Artificial Intelligence | Edureka Live

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AI & Deep learning with Tensorflow course: https://goo.gl/8qbeVK

This tutorial we will take you through Deep Learning concepts, how it is a way of achieving Artificial Intelligence. You will also learn how Deep Learning works along with some use-cases. Below were the topics we will cover in this live session:

1. Artificial Intelligence and its Subsets
2. Machine Learning and its Limitations
3. Deep Learning and its Mechanics
4. Deep Learning Use-Cases

Check our complete AI & Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE

Please write back to us at sales@edureka.co or call us at +91 88808 62004 for more information.

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Published in: Technology
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Deep Learning | A Step Closer To Artificial Intelligence | Edureka Live

  1. 1. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Agenda  What Is Artificial Intelligence ?  What Is Machine Learning ?  Limitations Of Machine Learning  Deep Learning To The Rescue  What Is Deep Learning ?  Deep Learning Applications
  2. 2. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Artificial Intelligence? Let’s begin by understanding various un-realistic applications of Artificial Intelligence in real life
  3. 3. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Artificial Intelligence Predicting Future
  4. 4. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Artificial Intelligence Predicting Future Chat Bots
  5. 5. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Artificial Intelligence Predicting Future Self-Driving Cars Chat Bots
  6. 6. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Artificial Intelligence Predicting Future Self-Driving Cars AI Eye Doctor Chat Bots
  7. 7. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Artificial Intelligence Predicting Future Self-Driving Cars AI Eye Doctor AI Music Composer Chat Bots
  8. 8. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Artificial Intelligence Predicting Future Self-Driving Cars AI Eye Doctor AI Music Composer AI Dream Machine Chat Bots
  9. 9. Copyright © 2017, edureka and/or its affiliates. All rights reserved. What Is Artificial Intelligence? Now, let’s understand what is Artificial Intelligence
  10. 10. Copyright © 2017, edureka and/or its affiliates. All rights reserved. What Is Artificial Intelligence?  The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and translation between languages. – source – Wikipedia  AI includes following areas of Specialization: – Game Playing – Expert Systems – Natural Language Processing – Neural Networks – Robotics Machine playing chess Siri Number plate recognition
  11. 11. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Subsets Of Artificial Intelligence Deep Learning is a subset of Machine Learning Machine Learning is a subset of AI Deep Learning uses neural networks to simulate human like decision making Artificial Intelligence Machine Learning Deep Learning
  12. 12. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Machine Learning Let’s understand what is Machine Learning
  13. 13. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Machine Learning  Machine Learning is a type of artificial intelligence (AI) that provide computers with the ability to learn without being explicitly programmed. Problem Statement: Determine the species of the flower Learn from the dataset
  14. 14. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Machine Learning  Machine Learning is a type of artificial intelligence (AI) that provide computers with the ability to learn without being explicitly programmed. New Input Sepal length, Sepal width, Petal Length, Petal Width Learn from the dataset Problem Statement: Determine the species of the flower
  15. 15. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Limitations Of Machine Learning Let’s understand, even when Machine Learning is present why we need Deep Learning
  16. 16. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Limitations Of Machine Learning Cannot solve crucial AI problems like NLP, Image recognition etc. Are not useful while working with high dimensional data, that is where we have large number of inputs and outputs Machine Learning Limitations Of Machine Learning
  17. 17. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Limitations Of Machine Learning Cannot solve crucial AI problems like NLP, Image recognition etc. Are not useful while working with high dimensional data, that is where we have large number of inputs and outputs
  18. 18. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Limitations Of Machine Learning One of the big challenges with traditional Machine Learning models is a process called feature extraction. For complex problems such as object recognition or handwriting recognition, this is a huge challenge. Deep Learning To The Rescue The idea behind Deep Learning is to build learning algorithms that mimic brain. Deep Learning models are capable to focus on the right features by themselves, requiring little guidance from the programmer. These models also partially solve the dimensionality problem.
  19. 19. Copyright © 2017, edureka and/or its affiliates. All rights reserved. How Deep Learning Works? Let’s understand the working of Deep Learning
  20. 20. Copyright © 2017, edureka and/or its affiliates. All rights reserved. How Deep Learning Works?  Deep Learning is implemented through Neural Networks.  Motivation behind Neural Networks is the biological Neuron. Dendrite: Receives signals from other neurons Cell Body: Sums all the inputs Axon: It is used to transmit signals to the other cells X1 X2 X3 Xn W1 W2 W3 Wn Transfer Function Activation Function Schematic for a neuron in a neural netNeuron Y
  21. 21. Copyright © 2017, edureka and/or its affiliates. All rights reserved. What Is Deep Learning? Input Layer Hidden Layer 1 Hidden Layer 2 Output Layer Deep Learning uses Deep Networks which are nothing but Neural Networks with multiple Hidden Layers.
  22. 22. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Deep Learning – Use Case Let’s look at a use-case where we can use DL for image recognition
  23. 23. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Deep Learning Example
  24. 24. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Deep Learning Use Case – Hand Written Digits We will take the same MNIST dataset. By using Multilayer Perceptron the efficiency can be increased to 99% Input Image (28x28) Filter Weights (5x5 pixels) (14x14 pixels) (16 channels) (7x7 pixels) (36 channels) Filter-Weights (5x5 pixels) 16 of these … 0. 00. 00. 10. 00. 00. 10. 00. 80. 00. 0 0 1 2 3 4 5 6 7 8 9 Fully-Connected Layer Output Layer Class Layer 1 Layer 2 (128 features)(10 features)
  25. 25. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Deep Learning Applications Let’s look at some applications of Deep Learning
  26. 26. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Deep Learning Some amazing and recent applications of Deep Learning are: • Automatic Machine Translation. • Object Classification in Photographs. • Automatic Handwriting Generation. • Character Text Generation. • Image Caption Generation. • Colorization of Black and White Images. • Automatic Game Playing. Face recognition Sar a Jes si Am y Priy a Ada m EmmaAndre w John
  27. 27. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Deep Learning - Google Lens  Google Lens is a set of vision-based computing capabilities that allows your smartphone to understand what's going on in a photo, video or a live feed.  For instance, point your phone at a flower and Google Lens will tell you on the screen which type of flower it is.  You can aim the camera at a restaurant sign to see reviews and other information.
  28. 28. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Applications Of Deep Learning - Machine Translation This is a task where you are given words in some language and you have to translate the words to the desired language say English.  This kind of translation is a classical example of Image recognition.
  29. 29. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Session In A Minute Why Artificial Intelligence? What is Artificial Intelligence? Subsets Of Artificial Intelligence Machine Learning to Deep Learning How Deep Learning Works? Deep Learning Applications
  30. 30. Copyright © 2017, edureka and/or its affiliates. All rights reserved.

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