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Machine Learning From Basic to Advanced [Free Online Course] - TechCracked

Machine Learning From Basic to Advanced

Learn to create Machine Learning Algorithms in Python Data Science enthusiasts. Code templates included.

This course includes:
  • 3 hours on-demand video
  • 30 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of completion


What you'll learn
  • Master Machine Learning on Python
  • Make accurate predictions
  • Make robust Machine Learning models
  • Use Machine Learning for personal purpose
  • Have a great intuition of many Machine Learning models
  • Know which Machine Learning model to choose for each type of problem
  • Use SciKit-Learn for Machine Learning Tasks
  • Make predictions using linear regression, polynomial regression, and multiple regression
  • Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, etc.


Description

Interested in the field of Machine Learning? Then this course is for you!

This course has been designed by Code Warriors the ML Enthusiasts so that we can share our knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way.

We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way:
  • Part 1 - Data Preprocessing
  • Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression.
  • Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
  • Part 4 - Clustering: K-Means, Hierarchical Clustering.


And as a bonus, this course includes Python code templates which you can download and use on your own projects.

Also See : Machine Learning & Deep Learning in Python & R

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