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Deep Learning, also known as deep structured learning or hierarchical learning, is a new area of Machine Learning research that is introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence.

The [course_title] course covers a basic introduction of Deep learning including applications to machine translation, image recognition, game playing, image generation. Upon completion, you will develop a solid understanding of the motivation for deep learning.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


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Course Credit: Massachusetts Institute of Technology

Course Curriculum

Introduction to Deep Learning 00:42:00
Sequence Modeling with Neural Networks 00:27:00
Convolutional Neural Networks 00:35:00
Deep Generative Modeling 00:44:00
Deep Reinforcement Learning 00:32:00
Deep Learning Limitations and New Frontiers 00:31:00
Issues in Image Classification 00:17:00
Faster ML Development with TensorFlow 00:19:00
Deep Learning – A Personal Perspective 00:32:00
Beyond Deep Learning: Learning+Reasoning 00:32:00
Computer Vision Meets Social Networks 00:34:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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