Udemy course Introduction To Machine Learning with Python for beginners by SKILL CURB
Introduction To Machine Learning with Python for beginners is the best Udemy course on the market. With this offer they will be able to greatly improve their knowledge and become more competitive within the IT & Software category. Therefore, if you are looking to improve your IT & Software skills we recommend that you download Introduction To Machine Learning with Python for beginners udemy course.
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- Author: SKILL CURB
- Course rating: 4.7
- Category: IT & Software
- Modality: Online
- Status: Available
- Idiom: English
Abouth SKILL CURB
SkillCurb is in the business of making an impact through creating easy to understand cutting edge technology courses at affordable prices. We are proud to have our co-instructors from around the world that are certified and have years of practical experience working for the fortune 500 companies build quality courses for our students.
What the udemy Introduction To Machine Learning with Python for beginners course teaches?
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 Show more Show less
The Complete Beginners Machine Learning Course with Python | Tons of lab exercises
More information about the course Introduction To Machine Learning with Python for beginners
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.