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Structuring Machine Learning Projects, deeplearning.ai

4.8
Оценки: 21,573
Рецензии: 2,455

Об этом курсе

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 learning I'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....

Лучшие рецензии

автор: AM

Nov 23, 2017

I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

автор: TR

Sep 22, 2018

This is a must course in the entire specialization. It covers the step by step procedure to approach and solve a problem. The case studies provided are real world problems which are so much helpful.

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Рецензии: 2,424

автор: Manish Nayak

Dec 15, 2018

very informative course

автор: 侯宇翔

Dec 14, 2018

Nice work but i think we need more guidelines of how to finish a successful machine learning project

автор: Jason DeBoever

Dec 14, 2018

5 start learning with 1 start video editing. An intern and Adobe Premiere with less than a week would fix it!

автор: Sai Kumar

Dec 14, 2018

this course very important other than previous courses because we need to understand the data and split the data set across the train, dev and test and making strategies for training the dataset using model. Thanks for this course.

автор: Wadigzon Diaz-Wong

Dec 14, 2018

excellent overview of best practices when organizing your ML project

автор: Archer Mo

Dec 13, 2018

Would be nicer if there are coding assignment that can guide us through some of the applications mentioned in the lecture

автор: Bhaskar Deka

Dec 13, 2018

Excellent course. Loved the case study format - good break from the other style of the rest of the courses.

автор: Oleksiy Simkiv

Dec 12, 2018

Valuable insight to ML system design

автор: Khoo Tze Sean

Dec 12, 2018

Great, it helps to build a good deep learning models quickly.

автор: shijiatongxue

Dec 12, 2018

Very nice and I have learned a lot from this course.Thank you Andrew Ng!