Search result for Learning methods Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 1,813 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Sample-based Learning Methods
by Martha White , Adam White- 4.7
-
![]()
![]()
![]()
![]()
![]()
Approx. 22 hours to complete
Learning from actual experience is striking because it requires no prior knowledge of the environment’s dynamics, yet can still attain optimal behavior. We will cover intuitively simple but powerful Monte Carlo methods, and temporal difference learning methods including Q-learning. Temporal Difference Learning Methods for Prediction Temporal Difference Learning Methods for Control...
Machine Learning
by Michael Littman , Charles Isbell , Pushkar Kolhe- 0.0
-
![]()
![]()
![]()
![]()
![]()
Approx. 4 months
lesson 1 Supervised Learning Machine Learning is the ROX Decision Trees Regression and Classification Neural Networks Instance-Based Learning Ensemble B&B Kernel Methods and Support Vector Machines (SVM)s Computational Learning Theory VC Dimensions Bayesian Learning Bayesian Inference lesson 2 Unsupervised Learning Randomized optimization Clustering Feature Selection Feature Transformation Information Theory lesson 3 Reinforcement Learning Markov Decision Processes Reinforcement Learning Game Theory...
Free
Learning and Development Methods
by Irina Ketkin- 4.6
-
![]()
![]()
![]()
![]()
![]()
3.5 hours on-demand video
You are not alone! Welcome to my course Learning and Development Methods – deciphering the practice of L&D. This course is part of a series in Advanced Learning and Development and it focuses on a wide range of methods L&D practitioners can use to help their organisations....
$11.99
Bayesian Methods for Machine Learning
by Daniil Polykovskiy , Alexander Novikov- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 33 hours to complete
People apply Bayesian methods in many areas: from game development to drug discovery. They give superpowers to many machine learning algorithms: handling missing data, extracting much more information from small datasets. We will also see applications of Bayesian methods to deep learning and how to generate new images with it. Introduction to Bayesian methods & Conjugate priors...
Practical Predictive Analytics: Models and Methods
by Bill Howe- 4.1
-
![]()
![]()
![]()
![]()
![]()
Approx. 7 hours to complete
Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems. Learning Goals: After completing this course, you will be able to: Explain and apply a set of unsupervised learning concepts and methods Comparing Classical and Resampling Methods...
Deep Reinforcement Learning
by Alexis Cook , Arpan Chakraborty , Mat Leonard , Luis Serrano , Cezanne Camacho , Dana Sheahan , Chhavi Yadav , Juan Delgado , Miguel Morales- 0.0
-
![]()
![]()
![]()
![]()
![]()
4 Months
The demand for engineers with reinforcement learning and deep learning skills far exceeds the number of engineers with these skills. Master the deep reinforcement learning skills that are powering amazing advances in AI. As such, it doesn't prepare you for a specific job, but instead expands your skills in the deep reinforcement learning domain....
Fundamentals of Machine Learning in Finance
by Igor Halperin- 3.8
-
![]()
![]()
![]()
![]()
![]()
Approx. 18 hours to complete
A learner with some or no previous knowledge of Machine Learning (ML) will get to know main algorithms of Supervised and Unsupervised Learning, and Reinforcement Learning, and will be able to use ML open source Python packages to design, test, and implement ML algorithms in Finance. Introduction to Fundamentals of Machine Learning in Finance...
Related searches
Practical Reinforcement Learning
by Pavel Shvechikov , Alexander Panin- 4.3
-
![]()
![]()
![]()
![]()
![]()
Approx. 26 hours to complete
Welcome to the Reinforcement Learning course. Reinforcement learning vs all Model-free methods Model-free reinforcement learning Approximate Value Based Methods Supervised & Reinforcement Learning Difficulties with Approximate Methods Policy-based methods Combining supervised & reinforcement learning Stability of policy-based vs value-based methods...
Modern Reinforcement Learning: Actor-Critic Methods
by Phil Tabor- 4.4
-
![]()
![]()
![]()
![]()
![]()
8 hours on-demand video
With the fundamentals out of the way, we move on to our harder projects: implementing deep reinforcement learning research papers. Why should we bother with actor critic methods when deep Q learning is so successful? Can the advances in deep Q learning be used in other fields of reinforcement learning? Reinforcement learning...
$11.99
Prediction and Control with Function Approximation
by Martha White , Adam White- 4.8
-
![]()
![]()
![]()
![]()
![]()
Approx. 22 hours to complete
You will see that estimating value functions can be cast as a supervised learning problem---function approximation---allowing you to build agents that carefully balance generalization and discrimination in order to maximize reward. -Understand how to use supervised learning approaches to approximate value functions Read Me: Pre-requisites and Learning Objectives Reinforcement Learning Textbook...
