A Practical Guide to Machine Learning with Python
Takeaway Skills
Learn fundamental principles and techniques of machine learning.
Understand the benefits and drawbacks of a variety of common machine learning methods.
The key premise of the course is to teach you how to code basic machine learning models.
Develop skills with using machine learning tools to solve real-world issues.
Learn the fundamentals of different learning paradigms (supervised, unsupervised, etc.).
Learn fundamental principles and techniques of machine learning.
Understand the benefits and drawbacks of a variety of common machine learning methods.
The key premise of the course is to teach you how to code basic machine learning models.
Develop skills with using machine learning tools to solve real-world issues.
Learn the fundamentals of different learning paradigms (supervised, unsupervised, etc.).
Course Overview
This course teaches you how to code basic machine learning models. The content is designed for beginners with general knowledge of machine learning, including common algorithms such as linear regression, logistic regression, SVM, KNN, decision trees, and more. If you need a refresher, ...
How You'll Learn
Hands-on coding environmentsYou don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.
Faster than videosVideos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.
No set-up requiredStart learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.
Progress you can showBuilt in assessments let you test your skills. Completion certificates let you show them off.
Hands-on coding environmentsYou don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.
Faster than videosVideos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.
No set-up requiredStart learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.
Progress you can showBuilt in assessments let you test your skills. Completion certificates let you show them off.
Course Contents
Introduction to Data ScrubbingData Scrubbing Operation: Removing VariablesData Scrubbing Operation: One-Hot EncodingData Scrubbing Operation: Drop Missing ValuesData Scrubbing Operation: Dimension ReductionQuizPCA Implementation Steps: 1 to 3PCA Implementation Steps: 4 to 6K-Means Clustering Implementation Steps: 1 to 3K-Means Clustering Implementation Steps: 4 to 6QuizImplementation of Linear RegressionLR Implementation Steps: 1 to 3LR Implementation Steps: 4 to 7LR Implementation Steps: 8 and 9QuizImplementation of Logistic RegressionLogistic Regression Steps: 1 to 4Logistic Regression Steps: 5 to 7Logistic Regression Steps: 8 and 9QuizImplementation of Support Vector MachinesSVM Implementation Steps: 1 to 7SVM Implementation Steps: 8 and 9QuizIntroduction to K-Nearest Neighborsk-NN Implementation Steps: 1 to 5k-NN Implementation Steps: 6 to 9QuizIntroduction to Tree-Based Methods1- Decision TreesDT Implementation Steps: 1 to 4DT Implementation Steps: 5 to 72- Random ForestsImplementation of Random Forest3- Gradient BoostingImplementation of Gradient Boosting ClassifierImplementation of Gradient Boosting RegressorQuiz
Takeaway Skills
Learn fundamental principles and techniques of machine learning.
Understand the benefits and drawbacks of a variety of common machine learning methods.
The key premise of the course is to teach you how to code basic machine learning models.
Develop skills with using machine learning tools to solve real-world issues.
Learn the fundamentals of different learning paradigms (supervised, unsupervised, etc.).
Learn fundamental principles and techniques of machine learning.
Understand the benefits and drawbacks of a variety of common machine learning methods.
The key premise of the course is to teach you how to code basic machine learning models.
Develop skills with using machine learning tools to solve real-world issues.
Learn the fundamentals of different learning paradigms (supervised, unsupervised, etc.).
Course Overview
This course teaches you how to code basic machine learning models. The content is designed for beginners with general knowledge of machine learning, including common algorithms such as linear regression, logistic regression, SVM, KNN, decision trees, and more. If you need a refresher, ...
How You'll Learn
You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.
Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.
Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.
Built in assessments let you test your skills. Completion certificates let you show them off.
You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.
Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.
Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.
Built in assessments let you test your skills. Completion certificates let you show them off.
Course Contents
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COURSE BY:
Oliver Theobald
