BL
5.0Reviewed Oct 16, 2016
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
Machine Learning Foundations: A Case Study Approach
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.
Status: Model Evaluation
Status: Artificial Intelligence and Machine Learning (AI/ML)
Course18 hours
Featured reviews
AH
5.0Reviewed Mar 27, 2022
very nice course.If you have basic knowledge of python datastructure then this course is best to start data science.All contents are beginner friendly which makes this course easily understandable.
SS
4.0Reviewed May 18, 2020
The course was very informative but I face a lot of problems in installing Graphlab and Turicreate. I request the Mentors please use the Pandas data frame in place of SFrame. The mentors are cool.
DS
5.0Reviewed Sep 27, 2015
Excellent course, with really good lectures, material and assignment. Plus the professors are really amazing and their enthusiasm is really refreshing and makes the class more interesting. Loved it!
DP
5.0Reviewed Feb 14, 2016
With a funny and welcoming look and feel, this course introduces machine learning through a hands-on approach, that enables the student to properly understand what ML is all about. Very nicely done!
KK
5.0Reviewed Feb 10, 2019
The course module is very clear and very useful for me to understand the ML concepts.Really excited about more features in the C_Stone project where i think we can do something for my organisation.
PM
5.0Reviewed Aug 18, 2019
The course was well designed and delivered by all the trainers with the help of case study and great examples.The forums and discussions were really useful and helpful while doing the assignments.
FA
5.0Reviewed Dec 26, 2022
Amazing course, lots of great ideas and amazing instructors, i really enjoyed it and looking forward to see what's coming next in the specialization. Also i am really greatfull for this information
BG
5.0Reviewed Mar 27, 2020
This course foundation for those who want to do specialization in Machine Learning. It's really very useful course, I recommend do this course If you want to do specialization in Machine Learning.
CL
5.0Reviewed Oct 7, 2019
This was good introductory course with challenging programming assignments that expanded and grounded the lecture materials. The forums also proved great support when needed, overall very satisfied.
DM
4.0Reviewed Apr 1, 2017
The Course was very neatly presented, although we used lots of predefined functions to work around Machine Learning Algorithms it was good to know about the concepts that was thought extremely well.
RM
4.0Reviewed Feb 2, 2022
I was very disappointed with the exclusion of the final courses and the capstone project. The most interesting part of specialization no longer exists and no plausible justification has been given.