Free online courseMachine Learning for complete beginners
Duration of the online course: 1 hours and 9 minutes
4.6
(5)
Explore machine learning basics in this free course. Learn regression, data visualization, and model performance—all in just over an hour!
In this free course, learn about
- Introduction and Foundations of Machine Learning
- Environment and Tooling Setup
- Linear Regression: From Data to Models
- Advanced Regression Concepts and Categorical Features
- Logistic Regression and Model Evaluation
Course Description
Explore the foundational concepts of machine learning with this free online course designed for complete beginners. Delve into the intriguing history of machine learning, understand various techniques, and get equipped with the essential tools needed for building machine learning models.
Start your learning journey by setting up your development environment, including Jupyter Notebooks, to seamlessly build regression models. Gain practical experience with projects in Python, starting with your first linear regression model.
Learn the art of data analysis, from cleaning datasets to visualizing data using Matplotlib. Understand the concept of linear regression, the importance of correlation, and how to implement linear and polynomial regression using Scikit-learn.
Dive deeper into categorical feature predictions and explore logistic regression for data classification. Prepare your data for analysis and measure regression performance using ROC curves. This course serves as an excellent stepping stone into the world of machine learning.
Course content
- Video class: Introduction to Machine Learning for Beginners [Part 1] | Machine Learning for Beginners 03m
- Exercise: What is the primary focus of the course discussed in the video?
- Video class: The history of Machine Learning [Part 2] | Machine Learning for Beginners 04m
- Exercise: What marked the beginning of the AI field in 1956?
- Video class: Techniques for Machine Learning [Part 3] | Machine Learning for Beginners 04m
- Exercise: What is the first step in starting a machine learning project?
- Video class: Setup your tools ready to build Machine Learning models [Part 4] | Machine Learning for Beginners 04m
- Exercise: What is the easiest way to start using Python for ML with minimal setup?
- Video class: Introduction to Regression models for Machine Learning [Part 5] | Machine Learning for Beginners 03m
- Exercise: Which type of regression is suitable for predicting a category?
- Video class: Set up Jupyter Notebooks to start building regression models [Pt 6] | Machine Learning for Beginners 05m
- Exercise: What is the primary purpose of using a virtual environment in the video tutorial?
- Video class: Your First Linear Regression Project in Python [Part 7] | Machine Learning for Beginners 04m
- Exercise: What is used to predict disease progression in the diabetes dataset using linear regression?
- Video class: How to Analyze and Clean a Dataset [Part 8] | Machine Learning for Beginners 03m
- Exercise: What is the main goal when analyzing and cleaning the pumpkin data set?
- Video class: How to Visualize Data with Matplotlib [Part 9] | Machine Learning for Beginners 03m
- Exercise: Which month is the cheapest to buy pumpkins according to the data visualization?
- Video class: Understanding Linear Regression [Part 10] | Machine Learning for Beginners 02m
- Exercise: What is the purpose of linear regression in data analysis?
- Video class: Looking for Correlation: The Key to Linear Regression [Part 11] | Machine Learning for Beginners 03m
- Exercise: What does a high positive correlation indicate between two variables?
- Video class: Linear and Polynomial Regression using Scikit-learn [Part 12] | Machine Learning for Beginners 05m
- Exercise: What is a limitation of using linear regression with the pumpkin dataset?
- Video class: Categorical Feature Predictions with Linear Regression [Part 13] | Machine Learning for Beginners 03m
- Exercise: What method is suggested for encoding categorical data into numerical values for regression models?
- Video class: Understanding Logistic Regression for Machine Learning Classification [Part 14] | ML for Beginners 03m
- Exercise: What is the primary purpose of logistic regression?
- Video class: Data Analysis and Preparation for Logistic Regression [Part 15] | Machine Learning for Beginners 05m
- Exercise: Which transformation method is used for converting pumpkin size categories into numerical values?
- Video class: Logistic Regression for classification of data [Part 16] | Machine Learning for Beginners 04m
- Exercise: What metric is often used when training models with unbalanced data?
- Video class: Analyzing Logistic Regression Performance with ROC Curves [Part 17] | Machine Learning for Beginners 04m
- Exercise: What does the ROC curve help analyze in a logistic regression model?
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This free course includes:
1 hours and 9 minutes of online video course
Digital certificate of course completion (Free)
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