Soledad Galli
Welcome to Deployment of Machine Learning Models, the most comprehensive machine learning deployments online course available to date. This course will show you how to take your machine learning models from the research environment to a fully integrated production environment.
What is model deployment?
Deployment of machine learning models, or simply, putting models into production, means making your models available to other systems within the organization or the web, so that they can receive data and return their predictions. Through the deployment of machine learning models, you can begin to take full advantage of the model you built.
Who is this course for?
If you’ve just built your first machine learning models and would like to know how to take them to production or deploy them into an API,
If you deployed a few models within your organization and would like to learn more about best practices on model deployment,
If you are an avid software developer who would like to step into deployment of fully integrated machine learning pipelines,
this course will show you how.
What will you learn?
We’ll take you step–by–step through engaging video tutorials and teach you everything you need to know to start creating a model in the research environment, and then transform the Jupyter notebooks into production code, package the code and deploy to an API, and add continuous integration and continuous delivery. We will discuss the concept of reproducibility, why it matters, and how to maximize reproducibility during deployment, through versioning, code repositories and the use of docker. And we will also discuss the tools and platforms available to deploy machine learning models.
Instructor Details
Courses : 3
Specification: Deployment of Machine Learning Models
|
28 reviews for Deployment of Machine Learning Models
Add a review
| Price | $18.99 |
|---|---|
| Provider | |
| Duration | 10.5 hours |
| Year | 2022 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$18.99
Bingoma Dieudonn –
oui
Ranjeet Kumar Verma –
great going so far…
Johnson chong –
It is a good and the most complete course for deployment Machine Learning in Backend!
Sai Santosh Pudi –
nice
Louis Vincent Boudreault –
Only describing what is already written in the jupyter notebook is boring and enifficient way of learning, clearly disappointed where the course is heading.
Stephen Kaiser –
So far the course looks great.
Yuzhou Song –
this course contains almost everything I’m eager to learn at this moment!
AFTI Watchdog –
Great run through the whole ML model deployment process. Clear and concise explanations along with good examples.
Prasad Pawar –
Its really best course not only for deployment but also for various coding standardization, inheritance or base classes, pipeline and many more things before deployment is actually done.
Michal Czapski –
This is an excellent course. I was preparing for a job interview and wanted to learn more about ML models deployment and this is how I found this gem. I wish more Udemy instructors were as thorough as Soledad and David. You can tell they are passionate about teaching. All the lectures are provided with slides and examples. They even tell you how to learn from this course depending what level of understanding of the problem you have. I also expanded my knowledge about some other aspect of ML/DS that I never fully explored. I couldn’t ask for more! Thank you!
Nitin Kumar –
Real life examples.Explained in full.
Pramod –
Its not so easy to keep the momentum with the course due to technical terms ,packages and complexity
Roma laxman Raj Jain –
I love the pace, and the way i can save notes
Jordan Siem –
Class has a lot of great content and so much information; it can be overwhelming. Originally, I took the class to basically find out what it takes to deploy a machine learning model and to know what were my different options for deployment. Kudos to you for all the different options! Although I really like the content, the instructors, and all the different options, I wasn’t too successful with deploying the different models because either some steps weren’t discussed or too much content was dependent upon earlier sections that I may have skipped. For example, if you want to deploy a model on AWS EC2 (section 12), you can’t just do that section you would actually need to do the docker section (section 11 if you don’t have that knowledge) and also the Heroku section (section 10) because some pieces are setup there as well. Basically, would have liked the class more if the deployment sections were more straightforward saying these are the steps needed to deploy this model if you didn’t complete them in other sections.
Salomon Orellana –
Seems very organized and relvevant, so far.
Alex Prado –
The title of the course is very misleading compared to the content of the course. I am looking for a course that will show me how to create the REST api, so actually deploying a ML model. I’m very disappointed:( hoping I can get my money back.
Gustavo Zantut –
good peaced, well detailed and complete
Olufemi Olajide –
I have bought all of Soledad’s Udemy courses and she is so brilliant at teaching, however, I feel this is a let down because this course made deploying models even more difficult than it is. Sections 5 and 6 are geared towards people with software engineering background and the instructor couldn’t just break things further for learners from other backgrounds. I hope the course is reviewed to accommodate a much wider audience.
Cristian Osorio Velasquez –
Very knowledgeable instructors! Quality teaching and content. Goes beyond basics as its the usually the case with Udemy courses
Jackiekuen –
First few sections are really good and clear, easy to follow. Explanations after section 6 could be more detailed and slower, especially CI/CD and versioning parts. The instructor can explained more on the design flow, why they code like this.
Eduardo Perez Denadai –
good course!
Tiago da Costa Abreu –
Very good course. Some further abstractions could have been performed if more effort was put into the course. However, it’s extremely difficult to find great industry professionals who also find the time to lecture, such as the two tutors in this course. Definitely recommend.
Prateek –
Awesome…Awesome….Awesome Soledad please continue doing such a fabulous work, enabling students like us to grow professionally from your courses. I have been enrolled on all your courses and they are just superb and full of gold mine knowledge.
Danxu688 –
This is a good course that has lots of things to learn. However, the Chris’ deployment part is not well integrated with Sole’s part. Started with section 8, the presentation slides downloaded are not corresponding to the videos, section 9 is empty, and you can not find section 11’s slides. This might be the fault of course developer.
Supun Hasitha –
Course is 9 hours long. First 4 hours it is about intro and creating the model. Then go in to deployment (which is actually we expect from the course). So to learn deployment we have 5 hours. In this 5 hours you have to learn IAAS deployments, PAAS deployments, Dockerization, CI/CD pipelines and many more. If you are a rocket scientist then this is possible. Since instructors want to cover many advance technologies within 5 hours, they skip lot of important things. At the end you are going to have a surface knowledge of all of these technologies. But after completing this course you can’t deploy your own model. Reason for this is instructors skip lot of important parts related to deployments. I can name few examples. Without knowing how to customize your own files like tox.ini, Procfile , Manifest.in, pyproject.toml and relations among these files, you will never be able to deploy your own model. So instructors miss the aim of the course which is teaching to deploy own ML models. (They have only spend around 5 minutes for giving some small introduction for these file types. They cover CI/CD within 1 hours and Docker under 20 minutes!) Another thing is lot of course materials and codes related to deployment part are outdated. They have recorded deployment sections in 2019 January. Its more than 2 and half years old. So you will get in to tons and tons of troubles even if you try to deploy the very same model that is provided in this course!! Also Instructors are not responsive in Q&A form. At this moment also I have a question lined up in the Q&A form that is asked more than 3 days ago. But did not get any response from instructors. I spend my money and time on this course but the return is not satisfactory. But I don’t want to waste my time by writing a bad review for someone else. I wrote this review as a heads up for the new students who wants to take this course in the future and as a suggestion for the instructors if they are willing to improve their course through students reviews.
Sanjay ANBU –
dis is what i was looking for to build a production ready machine learning api more than worth the money i spent this course gives exposure to lot of production and automation tools for ML api building
Brandon Brown –
Great to have an advanced course on Udemy
Gonzalo AD –
Nice to let you choose the pace in case you already know some things. Very clear and informative