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Machine Learning Practical: 6 Real-World Applications

Machine Learning - Get Your Hands Dirty by Solving Real Industry Challenges with Python
4.5
4.5/5
(2,452 reviews)
18,378 students
Created by

9.6

Classbaze Grade®

10.0

Freshness

8.8

Popularity

9.4

Material

Machine Learning - Get Your Hands Dirty by Solving Real Industry Challenges with Python
Platform: Udemy
Video: 8h 38m
Language: English
Next start: On Demand

Best Machine Learning classes:

Classbaze Rating

Classbaze Grade®

9.6 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

10.0 / 10
This course was last updated on 6/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

8.8 / 10
We analyzed factors such as the rating (4.5/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

9.4 / 10
Video Score: 8.9 / 10
The course includes 8h 38m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 5 hours 48 minutes of 749 Machine Learning courses on Udemy.
Detail Score: 9.9 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

4 articles.
0 resource.
0 exercise.
0 test.

In this page

About the course

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.
 
There are most exciting case studies including:
●      diagnosing diabetes in the early stages
●      directing customers to subscription products with app usage analysis
●      minimizing churn rate in finance
●      predicting customer location with GPS data
●      forecasting future currency exchange rates
●      classifying fashion
●      predicting breast cancer
●      and much more!
 
All real.
All true.
All helpful and applicable.
And as a final bonus:
 
In this course we will also cover Deep Learning Techniques and their practical applications.
So as you can see, our goal here is to really build the World’s leading practical machine learning course.
If your goal is to become a Machine Learning expert, you know how valuable these real-life examples really are. 
They will determine the difference between Data Scientists who just know the theory and Machine Learning experts who have gotten their hands dirty.
So if you want to get hands-on experience which you can add to your portfolio, then this course is for you.
Enroll now and we’ll see you inside.

What can you learn from this course?

✓ You will know how real data science project looks like
✓ You will be able to include these Case Studies in your resume
✓ You will be able better market yourself as a Machine Learning Practioneer
✓ You will feel confident during Data Science interview
✓ You will learn how to chain multiple ML algorithms together to achieve the goal
✓ You will learn most advanced Data Visualization techniques with Seaborn and Matplotlib
✓ You will learn Logistic Regression
✓ You will learn L1 Regularization (Lasso)
✓ You will learn Random Forest Classifier

What you need to start the course?

• You need to know Python (Machine Learning A-Z level is enough) in order to complete this course.
• You need to know how to set up your working environment (Anaconda, Jupyter Notebook, Spyder)
• This should not be your first Machine Learning course. You need to understand main concepts.

Who is this course is made for?

• Data Science and Machine Learning enthusiasts who want to understand how real data science projects look like.
• Anyone with Machine Learning and Python knowledge who wants to practice their skills

Are there coupons or discounts for Machine Learning Practical: 6 Real-World Applications ? What is the current price?

The course costs $14.99. And currently there is a 82% discount on the original price of the course, which was $84.99. So you save $70 if you enroll the course now.
The average price is $13.6 of 749 Machine Learning courses. So this course is 10% more expensive than the average Machine Learning course on Udemy.

Will I be refunded if I'm not satisfied with the Machine Learning Practical: 6 Real-World Applications course?

YES, Machine Learning Practical: 6 Real-World Applications has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

Currently we could not find a scholarship for the Machine Learning Practical: 6 Real-World Applications course, but there is a $70 discount from the original price ($84.99). So the current price is just $14.99.

Who will teach this course? Can I trust Kirill Eremenko?

Kirill Eremenko has created 44 courses that got 27,789 reviews which are generally positive. Kirill Eremenko has taught 295,730 students and received a 4.6 average review out of 27,789 reviews. Depending on the information available, we think that Kirill Eremenko is an instructor that you can trust.
Professor & Best-selling Instructor, 250K+ students
Ryan Ahmed is a best-selling Udemy instructor who is passionate about education and technology. Ryan’s mission is to make quality education accessible and affordable to everyone. Ryan holds a Ph.D. degree in Mechanical Engineering from McMaster* University, with focus on Mechatronics and Electric Vehicle (EV) control. He also received a Master’s of Applied Science degree from McMaster, with focus on Artificial Intelligence (AI) and fault detection and an MBA in Finance from the DeGroote School of Business. 
Ryan held several engineering positions at Fortune 500 companies globally such as Samsung America and Fiat-Chrysler Automobiles (FCA) Canada. Ryan has taught several courses on Science, Technology, Engineering and Mathematics to over 280,000+ students globally. He has over 25 published journal and conference research papers on state estimation, AI, Machine learning, battery modeling and EV controls. He is the co-recipient of the best paper award at the IEEE Transportation Electrification Conference and Expo (iTEC 2012) in Detroit, MI, USA. 
Ryan is a Stanford Certified Project Manager (SCPM), certified Professional Engineer (P.Eng.) in Ontario, a member of the Society of Automotive Engineers (SAE), and a member of the Institute of Electrical and Electronics Engineers (IEEE). He is also the program Co-Chair at the 2017 IEEE Transportation and Electrification Conference (iTEC’17) in Chicago, IL, USA.
* McMaster University is one of only four Canadian universities consistently ranked in the top 100 in the world.


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9.6

Classbaze Grade®

10.0

Freshness

8.8

Popularity

9.4

Material

Platform: Udemy
Video: 8h 38m
Language: English
Next start: On Demand

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