Introduction To Machine Learning with Python
Udemy Coupon ED | Introduction To Machine Learning with Python
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What you'll learn
- Fundamentals of Python
- Fundamentals of Machine Learning
- Learn machine learning, its algorithms and application
- Machine Learning Workflow
- Learn about Python Packages for Machine Learning
- Classification, regression, clustering, anomaly detection
- Exploratory Data Analysis and Visualization
- How machines learn from data
- Different types of machine learning models and how to choose among them
- Supervised, unsupervised, reinforcement, and transfer learning
- How to collect and prepare data suitable for training and testing machine learning models
This Complete Beginners Machine Learning Course
- is a carefully designed course for absolute beginners to intermediate
level audiences. The course is designed visually with interesting and
clear code examples that anybody can take this course even without any
prior programming experience. First few modules are designed to enable
audiences to understand the foundational topics of Machine Learning
(i.e., ML tools, techniques, Maths behind ML). Once students get the
grip on ML, then they are taken to the Python and ML world. You can
learn the course at your pace and practice the exercises provided at the
end of the topics
Each section of the course is linked to the previous one in terms of utilizing what was already learned and each topic is supplied with lots of examples which will help students in their process of learning.
Throughout the course, the code examples are demonstrated using the popular tool Jupyter Notebook.
We recommend you to download the latest version (3.6) of Python from the Anaconda Distribution website covered in this course.
If you have any suggestions on topics that have not been covered, you can send them via private message. I will do my best to cover them as soon as possible.
Each section of the course is linked to the previous one in terms of utilizing what was already learned and each topic is supplied with lots of examples which will help students in their process of learning.
Throughout the course, the code examples are demonstrated using the popular tool Jupyter Notebook.
We recommend you to download the latest version (3.6) of Python from the Anaconda Distribution website covered in this course.
If you have any suggestions on topics that have not been covered, you can send them via private message. I will do my best to cover them as soon as possible.
Who this course is for:
- Anyone who wants to learn about Machine Learning and Python
- Software Engineers
- IT operations
- Technical managers
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