Hands-on TensorFlow with Artificial Intelligence
A practical approach to deep learning and deep reinforcement learning for building real-world applications using TensorFlow
TensorFlow is one of the most commonly used frameworks for Deep Learning and AI. This course will be your guide to understand and learn the concepts of Artificial intelligence by applying them in a real-world project with TensorFlow.
This course will show you how to combine the power of Artificial Intelligence and TensorFlow to develop some exciting applications for the real world. This course will take you through all the relevant AI domains, tools, and algorithms required to build optimal solutions and will show you how to implement them hands-on. You will then be taken through techniques such as reinforcement learning, heuristic searches, neural networks, Computer Vision, OpenAI Gym, and more in different stages of your application. This course will show you how to implement AI practically using TensorFlow models and how it eases the way you interact with the technology.
You will learn how TensorFlow can be used to analyze a variety of data sets and will learn to optimize various AI algorithms. By the end of the course, you will have learned to build intelligent apps by leveraging the full potential of Artificial Intelligence with TensorFlow
Your Instructor
Hi! We are UpDegree, providing high quality interactive course.
We are the team of 100+ instructor over the globe. Adel (Oxford), Anand (Standford), Akash (IITB), Rajib (IITK), Partha (IITM) are few of them.
Updegree courses are different, In each and every course you not only get the videos lectures but you also get quiz,code,assignment etc to test your practical understanding!
Course Curriculum
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StartIntroduction and Outline (7:22)
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StartThe Current State of Artificial Intelligence (4:33)
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StartSetting Up the Environment for Deep Learning (7:29)
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StartAn Intro to Transfer Learning: Skin Cancer Classification (8:24)
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StartFundamentals of Object Localization and Detection (5:56)
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StartFundamentals of Object Localization and Detection (5:59)
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StartUnravelling Adversarial Learning and Generative Adversarial Nets (3:28)
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StartGenerating Handwritten Digits Using GANs (7:52)
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StartGenerating New Pokemons Using a DCGAN (1:33)
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StartSuper-Resolution Generative Adversarial Networks (4:45)
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StartIntroduction to Reinforcement Learning (11:57)
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StartIntroduction to Reinforcement Learning (4:28)
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StartDeep Q-Learning: Building a Game Bot That Plays the Classic Atari Games (4:05)
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StartDeep Reinforcement Learning with Policy Gradient - AI that Plays Pong (4:22)