Machine Learning

Machine Learning

Machine learning is the science of programming computers so they can learn from data. It is a subfield of artificial intelligence. Machine learning is closely related to computational statistics, which also focuses on prediction-making through the use of computers.

69 Skills|6 Courses
Supervised Learning: Regression
Supervised Learning: Regression
Supervised Learning: Regression
Supervised Learning: Regression
Intermediate
152 Learned
scikit-learnMachine Learning
Supervised learning. If you are hearing or reading this term for the first time, then it may be completely unclear what it means. Don't worry. In this lab, you will get a comprehensive understanding of supervised learning; and, in the next chapter of the experiment, you will learn to use supervised learning to complete data prediction.
7 Labs
Introduction to Supervised LearningStart
Linear RegressionStart
Prediction for Beijing Housing PricesStart
Polynomial Regression Pro Start
Prediction for Bitcoin Price Pro Start
Ridge Regression and Lasso Regression Pro Start
Calculation of Ridge Regression Coefficient Pro Start
Supervised Learning: Classification
Supervised Learning: Classification
Intermediate
25 Learned
scikit-learnMachine Learning
During this course, we will continue to learn another important application in supervised learning - solving classification problems. In the following lessons, you will be exposed to: logistic regression, K-nearest neighbor algorithm, naive Bayes, support vector machine, perceptron and artificial neural network, decision tree and random forest, and bagging and boosting methods. The course will start with the principle of each of these methods. You are supposed to fully understand the implementat
Lab
Unsupervised Learning: Clustering
Unsupervised Learning: Clustering
Intermediate
23 Learned
scikit-learnMachine Learning
In this course, you will fully understand unsupervised learning and learn to use unsupervised learning to perform data clustering.
Lab
Quick Start with TensorFlow
Quick Start with TensorFlow
Intermediate
50 Learned
TensorFlowMachine Learning
In this course, you will learn the basic concepts and syntax of TensorFlow 2, and how to use TensorFlow 2 to implement deep learning algorithms.
Lab
Foundations of Deep Learning
Foundations of Deep Learning
Intermediate
34 Learned
Machine LearningTensorFlow
In this course, you will learn the basic concepts of deep learning, including the basic principles of neural networks, the basic principles of TensorFlow, Keras and PyTorch, and the basic principles of linear regression, logistic regression, and multi-layer neural networks. You will also learn how to use TensorFlow, Keras and PyTorch to build a linear regression model, a logistic regression model, and a multi-layer neural network model.
Lab
Machine Learning Practice Plus
Machine Learning Practice Plus
Beginner
0 Learned
Machine Learning
In this course, You will practice more labs of Machine Learning. This will help you to master the skills more deeply.
Lab
Unlock Your Machine Learning Skills
Completed 0
Locked 69