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Description

The most advanced phenomenon in the history of computer generations is the technological development in the field of Artificial Intelligence (AI). AI is basically the concept in which machines develop the ability to simulate natural intelligence and carry out tasks “smartly”, while Machine Learning is an application of AI aiming to learn from data for a machine to maximize its performance. These interconnected concepts are covered in this foundation course. With 72 lectures, this tutorial provides the basics of Deep Learning by giving an insight of Convolutional Neural Networks and Recurrent Neural Networks, all by using TensorFlow.

  • Access 72 lectures & 6 hours of content 24/7
  • Gain a complete understanding of Convolutional Neural Networks, Recurrent Neural Networks & other Deep Architectures along w/ their uses in complex raw data using TensorFlow
  • Develop your expertise through case-studies, practice modules & real-time projects
  • Apply these concepts at work to handle Classification & Regression problems

Note: Software NOT included.

Data visualization means representing the data in a visual format. Visual formats include graphs, charts, and pictograms. It’s of great advantage to learn to deploy data visualization through Python using Matplotlib. Matplotlib is a library of Python that helps in the viewing of the data. In this course, you will learn how to deploy various commands for creating multiple graphs, 3D scatter diagrams, and Pie Charts among others. You will also learn about actual geographical plotting using Matplotlib extension called Basemap.

  • Access 72 lectures & 7 hours of content 24/7
  • Visualize varied forms of 2D & 3D graphs, like bar charts, line graphs, scatter plots, and more
  • Learn various ways to visually present Python data
  • Learn about actual geographical plotting using Matplotlib extension called Basemap

Computer Vision is an interdisciplinary field of study dealing with enabling computers to process high-level, complex digital images and videos. This field includes methods for collecting, processing, interpreting and understanding images and videos automatically. Its principal objective is to process pictures critically the way a human eye does for various outcomes. With 72 lectures, the course provides a more in-depth understanding of the role of Convolutional Neural networks, the knowledge of transfer learning, object localization, object detection, and using TensorFlow. Finally, the course talks about segmentation.

  • Access 72 lectures & 5.5 hours of content 24/7
  • Understand the fundamentals of Computer Vision
  • Know the challenges in working w/ Real-World data
  • Learn about CNN-based models & transfer learning
  • Get data w/ Single Objects for Object Localization

Natural Language Processing, or NLP, is one of the most demanded technology today. It is a field of AI which allows machines to interpret and comprehend human language. Since it is being used in emails, advertisements, language translations, web searches and much more, it would be a great advantage to understand the processes involved in this field. With 72 lectures, this course provides an innovative methodology and sample exercises that will help you go deeper into Natural Language processing.

  • Access 72 lectures & 5.5 hours of content 24/7
  • Learn how to build Artificial Intelligence for automation
  • Gain a comprehensive knowledge of the various concepts of NLP
  • Identify NLP tasks in your day-to-day work

You are allowed to use this product only within the laws of your country/region. SharewareOnSale and its staff are not responsible for any illegal activity. We did not develop this product; if you have an issue with this product, contact the developer. This product is offered "as is" without express or implied or any other type of warranty. The description of this product on this page is not a recommendation, endorsement, or review; it is a marketing description, written by the developer. The quality and performance of this product is without guarantee. Download or use at your own risk. If you don't feel comfortable with this product, then don't download it.

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