Kirill Eremenko
So you know the theory of Machine Learning and know how to create your first algorithms. Now what?
There are tons of courses out there about the underlying theory of Machine Learning which don’t go any deeper – into the applications.
This course is not one of them.
Are you ready to apply all of the theory and knowledge to real life Machine Learning challenges?
Then welcome to “Machine Learning Practical”.
We gathered best industry professionals with tons of completed projects behind.
Each presenter has a unique style, which is determined by his experience, and like in a real world, you will need adjust to it if you want successfully complete this course. We will leave no one behind!
This course will demystify how real Data Science project looks like. Time to move away from these polished examples which are only introducing you to the matter, but not giving any real experience.
If you are still dreaming where to learn Machine Learning through practice, where to take real–life projects for your CV, how to not look like a noob in the recruiter’s eyes, then you came to the right place!
This course provides a hands–on approach to real–life challenges and covers exactly what you need to succeed in the real world of Data Science.
Instructor Details
Courses : 11
Specification: Machine Learning Practical: 6 Real-World Applications
|
23 reviews for Machine Learning Practical: 6 Real-World Applications
Add a review
| Price | $14.99 |
|---|---|
| Provider | |
| Duration | 8.5 hours |
| Year | 2022 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$14.99
Kishor V Kulkarni –
I have one other course from Hadlin on DataScience. (A Z). That course was really good so I had high expectations from this course. But overall feedback about this course is not good. Out of 6 applications, First 2 are good but rest have below issues 1. Audio and video (picture quality) is not good at all. 2. You can’t even see the code written on very well internet connectivity. 3. Some applications are just reading the slides and not much info. Sorry to say but this course disappointed me lot.
Raymond –
use cases are very fintech centric. Would like to see more variety of industries DS has been applied to.
Anoop Bhagat –
quite lucidly explained.
Anuja Fole –
The course is not up to the expectations. One loses interest in the middle of each section because of the datasets provided. These datasets are very different from the one used in the video. Also, your doubts are not cleared.
Dnyanashree Patil –
Really a different course. Can include similar hands on for learners. Looking for more such courses
Raj Gupta –
well explained in most simple way.
Arslan –
Awesome course. Focused on practical real world applications. Solid foundation for entering market
BELLES –
could use a little (just a few more min) on explaining some of the higher stats. explains python fairly well, but some of the stats is less intuitive
Roger Wang –
The first part of the course is pretty good, with a lot of charts and overall is very clear. The second part is good in terms of content, however, the audio quality is not that good as well as the lecturer used Spyder instead of Jupyter notebook, which is not so good for illustration purpose as compared to Jupyter notebook.
Smruti Prava Dash –
The audio quality is not good. And the presentation is not motivating.
Ashwini Shitole –
1. Case study 3 was far difficult to understand. should get answers to queries raised quickly. 2. Examples covered are really good but need more explanation on why selected model is the best suited or why instructor is performing said actions. 3. keras did not work on my machine till last use case so I could not run scripts for deep learnings. Please provide installation with latest and suitable versions for 2020
Param Sivalingam –
We are told that the cancer detection has 20 features but not enough explanation on how these features can be used in the classification of cancer in a machine learning algorith.
CHANDRABABU DANDI –
Quite interesting lectures and explanation is very well and understandable.
X W –
unclear accent
Mayank Sharma –
An amazing course to have a hands on practice on machine learning field
Carlos Eduardo Fraire Guerrero –
Looking a real world application of the machine learning is quite interesting. The instructor way of explaining is very clear.
Ingrid Bianka Garcia Lino –
easily to understand 🙂
Devi Wheeler –
This course deep dives in several aspects of machine learning, thank you for being so detailed.
Gene Stebley –
Yes, because you learn something different and unique from each instructor
Daniel Socoloff –
Some instructors were clear, others not so clear.
Yash Krishan Kaushik –
The presentation was great and highly visual.
Mohammed Yaqoob –
Sound is bad
Rohaan George N –
The contents are mainly focussed on beginners with the common dataset