Machine Learning Practical: 6 Real-World Applications The name of a training course from the Udemy site that works with 6 real-world applications to familiarize you with machine learning. Machine learning is a widely used branch of artificial intelligence that can prepare systems for learning by understanding and using specific techniques and algorithms. If you have already learned the basics of machine learning including algorithm building, you can use this course to learn how to work on real projects.
This course will show you what a real Data Science project looks like. During this course, you will be working on projects such as early detection of diabetes, guiding customers towards collaborative products, reducing financial loss rates, predicting customer positioning using GPS information, estimating future currency conversion rates, modes of classification , Predicting Breast Cancer, etc. You will work with Python and learn deep learning techniques.
Courses taught in this course:
- Work on real Data Science projects
- Use projects of this course as resume
- Learn about advanced machine learning topics
- Combine several ML algorithms to achieve the goals
- Learn information visualization techniques using Seaborn and Matplotlib
- Logistic Regression Training
- Set L1
- Random forest classification
Machine Learning Practical Course Specifications:
- English language
- Duration: 8 hours 37 minutes
- Number of lessons: 82
- Level of education: Intermediate
- Instructor: Kirill Eremenko, Hadelin de Ponteves, dr. Ryan Ahmed, Ph.D., MBA, SuperDataScience Team, Rony Sulca
- File format: mp4
Machine Learning Practical course headings
Prerequisites of Machine Learning Practical course
- You need to know Python (Machine Learning AZ level is sufficient) 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 the main concepts.
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