Structuring Machine Learning Projects

If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language

( 810 Reviews )

Created by: Andrew Ng

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Overall Score : 100 / 100

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Course Description

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how.Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience.After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error- Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance- Know how to apply end-to-end learning, transfer learning, and multi-task learningI've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time.This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization.

Time: 7h

Instructor Details

Andrew Ng

5.0 Rating
810 Reviews

Andrew Ng is Co-founder of Coursera, an and Adjunct Professor of Computer Science at Stanford University. His machine learning course is the MOOC that had led to the founding of Coursera! In 2011, he led the development of Stanford University's main MOOC (Massive Open Online Courses) platform and also taught an online Machine Learning class to over 100,000 students, thus helping launch the MOOC movement and also leading to the founding of Coursera.Ng also works on machine learning, with an emphasis on deep learning. He had founded and led the "Google Brain" project, which developed massive-scale deep learning algorithms. This resulted in the famous "Google cat" result, in which a massive neural network with 1 billion parameters learned from unlabeled YouTube videos to detect cats. Until recently, he led Baidu's ~1300 person AI Group, which developed technologies in deep learning, speech, computer vision, NLP, and other areas.

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