This post presents a summary of a series of tutorials covering the exercises from Andrew Ng's machine learning class on Coursera. Instead of implementing the exercises in Octave, the author has opted to do so in
The best way to learn is to practice and answer exercises. We have started this section for those (beginner to intermediate) familiar with Python and Scikit-learn. Hope these exercises help you to improve your Machine Learning skills using Scikit-learn. Currently, the following sections are avail...
Why Is Python Important to Machine Learning?So, why must I learn Python if all I want is to develop my machine learning solutions?You don’t. But you will find your life much easier if you are competent with Python.Python is an amazing programming language. It is simple to read but ...
Why Is Python Important to Machine Learning?So, why must I learn Python if all I want is to develop my machine learning solutions?You don’t. But you will find your life much easier if you are competent with Python.Python is an amazing programming language. It is simple to read but ...
The Iris dataset is famous in machine learning, commonly used for classification tasks. It contains features related to iris flowers and their species, making it a good example for machine learning exercises. load_digits() loads another dataset, the Digits dataset. load_diabetes() loads the ...
Deploying machine learning models in production Personal help We are happy to offer on-the-spot problem-solving after each day of the training for you to ask one-on-one questions — whether about the course content and exercises or about specific problems you face in your work and how to so...
to strengthen your programming skills, this course provides a comprehensive introduction to Python and essentials of machine learning , offering practical experience, hands-on coding exercises, and the opportunity to develop a strong foundational understanding of key concepts to advance your learning ...
As such, the systematic structure of the book, along with the many examples and exercises presented, will help the readers to better grasp the content and be equipped with the practical skills required in day-to-day machine learning applications....
Serg skillfully balances theory with real-world applications, making this a valuable resource for anyone seeking a deeper understanding of model transparency in the ML landscape.Bonus: there's a GitHub repository with all Python exercises covered in each chapter, making it hands-on and practical. ...
Tom Mitchell Machine Learning Lectures You don't need all of the notes and videos at this point. A valid strategy involves moving forward to particular exercises below, and referencing applicable sections of the above notes and videos when appropriate. For example, when you come across an exercis...