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Artificial Intelligence with Python – Deep Neural Networks

80 minutes of course content

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$19.99 (taxes calculated at checkout)

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Course Description

Learn different Artificial Intelligence learning techniques with neural networks

About This Video

  • Learn the fundamentals of Deep Learning and use them to build intelligent systems
  • Solve real-world problems such as face detection, handwriting recognition, and more
  • Work with reinforcement learning, convolutional networks, and other deep learning concepts

In Detail

The course is an introduction to the basics of deep learning methods. We will start with object detection and tracking, in which we will track faces, objects and eyes. We will then build a neural network and an OCR. We will then learn how to build learning agents that can learn from interacting with the environment. We will use Deep Learning with Convolutional Neural Networks, and use TensorFlow to build neural networks. We will then build an image classifier using convolutional neural networks.

      After taking this course, you will be able to:

      • Build applications based on deep learning algorithms

      • Learn how reinforcement learning works
      • Detect and track objects using different algorithms 

      This course is for professionals within the following business functions:

      • Everyone is welcome in this course.

          1. Object Detection and Tracking - 28 Minutes

            1. The Course Overview
            2. Installing OpenCV
            3. Frame Differencing
            4. Tracking Objects Using Colorspaces
            5. Object Tracking Using Background Subtraction
            6. Building an Object Tracker Using the CAMShift Algorithm
            7. Optical Flow Based Tracking
            8. Face Detection and Tracking
          2. Artificial Neural Networks - 22 Minutes

            1. Introduction to Artificial Neural Networks
            2. Building a Perceptron Based Classifier
            3. Constructing Single and Multilayer Neural Networks
            4. Building a Vector Quantizer
            5. Analyzing Sequential Data Using Recurrent Neural Networks
            6. Visualizing Characters in an Optical Character Recognition Database
            7. Building an Optical Character Recognition Engine
          3. Reinforcement Learning - 11 Minutes 

            1. What Is Reinforcement Learning?
            2. Creating an Environment
            3. Building a Learning Agent
          4. Deep Learning with Convolutional Neural Networks - 19 Minutes

            1. What are Convolutional Neural Networks?
            2. Building a Perceptron-Based Linear Regressor
            3. Building an Image Classifier Using a Single Layer Neural Network
            4. Building an Image Classifier Using a Convolutional Neural Network

          About the Expert



          Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work. With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now. From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer. Packt courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.
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