Supervised Machine Learning for beginners

kick start your machine learning journey with supervised learning for beginners, python, jupyter and scikit-learn!

Supervised Machine Learning for beginners
Supervised Machine Learning for beginners

Supervised Machine Learning for beginners udemy course

kick start your machine learning journey with supervised learning for beginners, python, jupyter and scikit-learn!

What you'll learn:

  • Regression and Classification Algorithms
  • Using sk-learn and Python to implement supervised machine learning techniques
  • K-nearest neighbors for both classification and regression
  • Naïve Bayes
  • Ridge and Lasso Regression
  • Decision Trees
  • Random Forests
  • Support Vector Machines
  • Practical case studies for training, testing and evaluating and improving model performance
  • Cross-validation for parameter optimization
  • Learn to use metrics such as Precision, Recall, F1-score, as well as a confusion matrix to evaluate true model performance
  • You will dive into the theoretical foundation behind each algorithm with the aid of intuitive explanation of formulas and mathematical notions

Requirements:

  • The course is open to everyone who wants to learn data science.
  • You’ll need to install Anaconda and Jupyter Notebook. We will show you how to do that step by step.

Description:

If you are a developer, an architect, an engineer, a techie, an IT enthusiast, a student or just a curious person, if you are interested in taking on machine learning but you are not too sure where to start, this is probably the right course for you!!

In this course, we start with the basics and we explain the concept of supervised learning in depth, we also go over the various types of problems that can be solved using supervised learning techniques. Then we get more hands-on and illustrate some concepts relative to data preparation and model evaluation with bits of code that you can easily reuse. And last, we actually train and evaluate several models based on the most common machine learning algorithms for supervised learning such as K-nearest neighbors, logistic regression, decision trees and random forests.

I hope that you find this course fun and easy to follow and that it gives you the machine learning background you need to kick start your journey and be successful in this field!

Who this course is for:

Course Details:

  • 5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of completion

Supervised Machine Learning for beginners udemy free download

kick start your machine learning journey with supervised learning for beginners, python, jupyter and scikit-learn!

Demo Link: https://www.udemy.com/course/supervised-machine-learning-for-beginners/