Search result for Supervised and unsupervised learning Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 229 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Machine Learning: Clustering & Retrieval
by Emily Fox , Carlos Guestrin- 4.6
-
![]()
![]()
![]()
![]()
![]()
Approx. 17 hours to complete
A reader is interested in a specific news article and you want to find similar articles to recommend. Learning Outcomes: By the end of this course, you will be able to: -Compare and contrast supervised and unsupervised learning tasks. Hope for unsupervised learning, and some challenge cases Learning LDA model via Gibbs sampling...
24h Pro data science in R
by Francisco Juretig- 3.6
-
![]()
![]()
![]()
![]()
![]()
18.5 hours on-demand video
This course explores several modern machine learning and data science techniques in R. We showcase a wide array of statistical and machine learning techniques. Supervised ML problems using the CARET packageData processing using sqldf, caret, etc. The teaching approach is to briefly introduce each technique, and focus on the computational aspect....
$12.99
Introduction to Deep Learning
by Evgeny Sokolov , Зимовнов Андрей Вадимович , Alexander Panin , Ekaterina Lobacheva , Nikita Kazeev- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 34 hours to complete
The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding. Derivatives of MSE and cross-entropy loss functions. Overfitting problem and model validation What Deep Learning is and is not Unsupervised representation learning Unsupervised learning: what it is and why bother...
Cluster Analysis and Unsupervised Machine Learning in Python
by Lazy Programmer Team- 4.6
-
![]()
![]()
![]()
![]()
![]()
8 hours on-demand video
Cluster analysis is a staple of unsupervised machine learning and data science. This is where unsupervised machine learning comes into play. Next, because in machine learning we like to talk about probability distributions, we’ll go into Gaussian mixture models and kernel density estimation, where we talk about how to "learn" the probability distribution of a set of data....
$29.99
Machine learning with Scikit-learn
by Francisco Juretig- 3.6
-
![]()
![]()
![]()
![]()
![]()
6.5 hours on-demand video
We'll explain what are the differences between AI, machine learning (ML), statistics, and data mining. In essence, machine learning can be divided into two big groups: supervised and unsupervised learning. In supervised learning we will have an objective variable (which can be continuous or categorical) and we want to use certain features to predict it....
$11.99
Solve Business Problems with AI and Machine Learning
by Renée Cummings- 0.0
-
![]()
![]()
![]()
![]()
![]()
Approx. 11 hours to complete
Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. Solve Business Problems with AI and Machine Learning Course Introduction Concept Drift and Transfer Learning Differences Between Traditional Programming and Machine Learning Differences Between Supervised and Unsupervised Learning Identify appropriate applications of AI and machine learning within a given business situation....
Data Science Fundamentals for Data Analysts
by Emma Freeman , Mark Roepke- 0.0
-
![]()
![]()
![]()
![]()
![]()
Approx. 19 hours to complete
Module and Lesson Introduction Supervised and Unsupervised Learning A Review of Supervised Learning and Regression Machine Learning Solutions Discussion Intro Measuring Success and Constraints Machine Learning Solutions Apply foundational data science concepts and techniques to solve these real-world problems. Design, execute, assess, and communicate the results of your very own data science projects....
Related searches
Introduction to Trading, Machine Learning & GCP
by Jack Farmer , Ram Seshadri- 4
-
![]()
![]()
![]()
![]()
![]()
Approx. 9 hours to complete
In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. What is AI and ML ? Supervised Learning and Regression Welcome to Introduction to Trading, Machine Learning and GCP AI and Machine Learning Supervised Learning with BigQuery ML Introduction to Neural Networks and Deep Learning...
Hands-on Text Mining and Analytics
by Min Song- 3.9
-
![]()
![]()
![]()
![]()
![]()
Approx. 13 hours to complete
This course provides an unique opportunity for you to learn key components of text mining and analytics aided by the real world datasets and the text mining toolkit written in Java. 4 How-to-do: normalization including tokenization and lemmatization 1 Explanations of sentiment analysis with supervised learning 2 Explanations of sentiment analysis with unsupervised learning...
Teaching Impacts of Technology: Data Collection, Use, and Privacy
by Beth Simon- 4.6
-
![]()
![]()
![]()
![]()
![]()
Approx. 13 hours to complete
Technology and Computing Concepts: AI vs ML, Supervised vs Unsupervised learning, Neural Networks, Recommender systems, Speech recognition In terms of CSTA K-12 computer science standards, we’ll primarily cover learning objectives within the “impacts of computing” concept, while also including some within the “networks and the Internet” concepts and the “data and analysis” concept....
Previous
