Lawrence Carin
This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. In addition, we have designed practice exercises that will give you hands–on experience implementing these data science models on data sets. These practice exercises will teach you how to implement machine learning algorithms with TensorFlow, open source libraries used by leading tech companies in the machine learning field (e.g., Google, NVIDIA, CocaCola, eBay, Snapchat, Uber and many more). Duke University has about 13,000 undergraduate and graduate students and a world–class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
Instructor Details
Courses : 1
Specification: Introduction to Machine Learning
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38 reviews for Introduction to Machine Learning
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 16 hours |
| Year | 2018 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
FREE
Sameera K –
Very Good course explaining the theoretical concepts related to deep learning . Thank you
Michael B –
Excellent course. Concepts such as gradient descent and convolutions as they pertain to neural networks are explained without going into the mathematical details but, in my opinion, are explained more intuitively and better, as compared to most other courses. The course does include some ungraded Jupyter notebooks exemplifying key elements of deep learning networks. Highly recommended to ‘cement’ understanding of neural networks.
Erica R –
This was a really great course for understanding the basics of machine learning through a lot of simple but relevant, real world examples.
KAVADIBALLARI V –
GOOD COURSE
Ayse U –
I like this introductory course, very good one to start to learn machine learning. I will definitely continue studying and re–watch the videos.
Shukshin I –
It was great to touch new professional area and to understand its fundamentals. The course gives a broad view on machine learning, so I think now I really understand, what the machine learning is and how to use it in my work and even my political investigations.
Tami Z –
Great Course! A very comprehensive and clear introduction to the field of ML.
Pranav R –
very good for getting started.
Abdul M –
I have a background in pathology and I wanted to understand how machine learning works so that I can take an active part in the changes within my field and understand what is happening. This course was an amazing experience of learning, for someone like me with no background in calculus or linear algebra.
Noah R –
Great course for beginners, did a lot to fill in the gaps in my knowledge. There could be a little more help with the actual coding parts of the project, the work done in ipython notebook is largely self–taught.
Lewis C L –
Much weaker than Stanford offerings. Strange buildup of topics for a breezy, but not particular accurate understanding. For example: multiple layers of a neural network is introduced before multiple category classification. Transfer learning is introduced incorrectly. The matrix representation of multiple features of an example with multiple examples is introduced very late in the course. The instructor is conscientious and seemingly knows the material despite using non–standard terminology. One wonders if he is primarily a teacher/researcher and rarely a practitioner. One wonders if Duke is a leader in machine learning research.
Tarun Y –
A very fine tuned Course,used as a warm up course for deep learning,highly recommended
Juan R –
It would be great to have more small practical exercises as it always reinforces the theory explained
PRADEEP K T –
Easy to understand about machine learning
Upul T –
Excellent introduction in to machine learning and paced ideally to keep the interest throughout the course. Ignites interest to the field.
Akhil K –
Very Interesting Course
Eric T –
Great course ! Pr Carin is clear enough to make you understand complex concepts like LSTM. The Math, calculus, algenra and prob are not too difficult. I enjoyed to follow this course ! To conclude a good introduction to ML to make you go deeper into the subject
Jonah P –
The course is a good balance between learning key concepts and doing coding, the coding being optional. The phrasing of quiz questions and answers were sometimes confusing.
Robin J –
Good way to start ML journe
Oscar S –
Excelente
Aliraza –
Simply Brilliant
Guido C –
Very good introductory course, I highly recommend it to anyone looking to get a flavour of the methods behind the recent advances in AI without going into super–technical details.
Antonio R C N –
Amazing course
Riley B –
I liked the pace and the tensor flow applications. This should be upgraded to TF 2.0 at some point. Also, I would’ve appreciated some GAN material.
Franco B –
Course provides the fundamental of machine learning techniques, representing the state of the art of image and text processing; some more examples could help in enforce the meaning and intermediate results in applying
Zeeshan L –
Best course
Sandeep D D –
Thanks
Sarah G –
Pretty good introduction to Machine Learning!
Santosh G –
It is very good contetnt and begin in Machin learning
Nitin S R –
Good ML Learning course
Reena P –
It was a very new topic for me but the video had lucid explanations to make it understand for a beginner like me. Thank you.
Madison S –
Excellent course! Very well organized and explained thoughtfully.
Marcus V C A –
It’s a basic course, but an useful one. It give us the fundamental concepts to dive in the subject.
Veerraju C –
Very good learning
Kartik G –
Although the course is great from a theoretical point of view, but it has two major flaws. First, it doesn’t provide the fundamentals of Machine Learning but instead directly moves to Deep Learning, although building those concepts from ground up. Also, from a practical point of view, this course is really lacking as there is not a single explanation video on any of the coding aspect of Deep Learning and the videos that even exist just ask us to read through the Documentation to learn the practical aspect.
Jin T –
Great course! Once you delve into it, you will love the professor’s lecture style and learn some great insight into deep learning topics.
Anurag S –
This course is an eye opener for anyone who wants to step or learn about Machine Learning. It provides various scenarios and the steps which you can apply to current real world problems. This course is a must for all the beginners.
Muhammad A D I M –
n o t g o o d .