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返回到 机器学习基础:案例研究

學生對 华盛顿大学 提供的 机器学习基础:案例研究 的評價和反饋

12,339 個評分
2,957 條評論


Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python....



Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much


Great course!\n\nEmily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.


276 - 机器学习基础:案例研究 的 300 個評論(共 2,870 個)

創建者 Ashar M


Great course, focused on practical learning and some of the widely used applications, such as sentiment analysis, product recommendations, image recognition etc. The videos are crisp and to the point and you will appreciate the amount of knowledge they pack in a very short time.

創建者 Genyu Z


This course is very useful. Firstly, it helps me to build a perfect python environment. Secondly, it teaches me how to use jupyter notebook correctly. Teachers are very kind, and I like their teaching ways. If I can build algorithm without graphlab, it will be more challenging.

創建者 Alberto V H


A very good introduction to foundations of machine learning. The learning methodology based on study cases is amazing and gripping and the ipython notebooks used in the practical sessions are very instructive. Strongly recommendable for everybody who want to start in this world

創建者 Andre J


These Machine Learning classes have been fantastic so far, really enjoying them. Very good coverage of topics and challenging exercises to drive home the learning. The effort put into developing the classes has been superb and I look forward to the rest of the specialization.

創建者 Haritz P


I really enjoyed this course. It's a very good introduction to Machine Learning. I already know a little bit of machine learning, R and Weka and I liked this course. I learned Machine Learning in Python and a little bit of NLP. I'm very excited to complete the specialization!!

創建者 Rohit G


I really loved the course ! It helped me greatly to gain an overall idea of the aspects of machine learning at the outset itself without confusing me with intricate details of the course and yet introducing to everything in there at a glance !

Really keeps you hungry for more !

創建者 Maria Z


Great course, thank you very much! I had no previous experience with ML or programming, that was quite challenging for me to pass the assignment, but it was possible The material is being taught by the tutors very clear. I'm sure to continue my education with further courses.

創建者 Zachary C


A great primer on the various high level concepts in machine learning and some general applications as well as good quick intro to graphlab create. I was originally apprehensive to use another data science tool outside of panadas, but now think graphlab create is even better.

創建者 Miguel A P L


Before taking this course I would not consider the topic as something that one could learn by himself.

The Course has opened my mind and has showed me that there is a lot to learn and study in order to fully master ML and AI in order to use it in the applications we can build.

創建者 Gurunath M K


It was truly informative course. At the end of the course, I am sure I can say I know the all the key concepts behind Machine Learning. In near future, my focus will be be try to implement in relevant use-cases around. Thanks Accenture LKM and Coursera for facilitating this.

創建者 Supriya N P K


Its a very basic course and a good start to learn Machine Learning.

Course was pretty easy to follow and the real world examples helped to visualize the applications of Machine Learning. Its highly recommended for the students who are completely new to the Machine Learning.

創建者 Puppala A S


The course was awesome and i am willing to learn all the courses present in this specialization.Both the tutors are great and their explanation was incredible . Actually this course period is of 6 weeks but I completed the whole course within a week because of the tutors .

創建者 Peter G


Very nice brief introduction into the field. Gives good overview of main concepts: 1) statements of problems in machine learning 2) approaches to finding solutions 3) methods to evaluate resulting solution . Systematic material presentation with good examples and analogies.

創建者 Zachary N


Great overview of machine learning techniques and practices at a high level! There is sufficient material here to go from no machine learning knowledge (and a general programming background) to being able to create and deploy machine learning models for use in applications.

創建者 Aman A


Awesome way of teaching that too from a well qualified faculty. Rather than imparting theoretical knowledge, great focus is on practical knowledge that's what I like about this Course. Thanks to Coursera for giving me this opportunity to get tutelage from such an erudite.

創建者 Mayuresh W


The course was well detailed and gave a good idea of what to expect when learning about machine learning and this specialization.

Covering each of the topics well with sufficient explanation and a small project was a great way to learn.

Looking forward to the next courses :)

創建者 Gerard Y


Very good overview, the lectures were enjoyable to follow, and brought good intuition on the topics with a good sense of what was possible. The exercises were of reasonable difficulty, and not too hard to set up, allowed to get a good feel of the potential of Turi Create.

創建者 gaoyu_xinghuo


Exclude the last part, the whole session gave us the clear picture about machine learning -- What the machine learning is , how machine learning works and how to use machine learning to change the world:)

I love the course, it gave me a lot. Thanks Emily and Carlos again.

創建者 Daniel R


It is a really well thought introduction for Machine Learning. It is almost unbelieveable that you could use every single technique in less than a month. Of course using a framework, but if you are really interested you could do them with open source tools.

It is amazing!

創建者 Arjun P


A very good course that gave me a jump start to machine learning application and got me right into coding the applications. This course takes a very different approach to teaching ML and I guess it works as it keeps me interested and makes me want more from this course.

創建者 alexandre l f


Case study base approach makes this course pragmatical and business oriented. A great team with good tools and exercise which deserves a 5.

Note : math's background is low (or more exactly far from the target of this course) and might be a blocking point at some stage.

創建者 Raphael K


Nice class, give a brief introduction to all the methods use in ML without going deep. If you just want to get an idea of what ML Technics are and how to implement them this course is for you. If you are want more technical details about ML this class is not for you.

創建者 Yaobang C


I am very grateful to the coursera platform for giving me the opportunity to learn, and I would also like to thank the two professors for their careful preparation of the wonderful lectures. I learned about machine learning and fell in love with ipynb, thanks again!

創建者 Jose N N P


Excellent course and very challenging, most importantly, I have learned a lot and I have a great understanding of what machine learning is. Dr. Carlos and Emily are great instructors, and indeed engaging as well as passionate. Looking forward to taking the next one.

創建者 Easton L


Emily and Carlos are really exciting teachers. This course covers fundamental concepts of Machine Learning and comes with very practical assignments. I've learned a lot from the this course and I believe it will make me ready for more challenging work in the future.