Home AI Courses Unsupervised Learning, Recommenders, Reinforcement Learning

Unsupervised Learning, Recommenders, Reinforcement Learning

(0 reviews)

Learn to apply unsupervised learning techniques, build recommender systems, and develop deep reinforcement learning models.

Key AI Functions:Anomaly Detection,Unsupervised Learning,Reinforcement Learning,Collaborative Filtering,Recommender Systems

Description

Reviews

Alternative Tools

Description for Unsupervised Learning, Recommenders, Reinforcement Learning

Employ unsupervised learning methodologies, such as anomaly detection and clustering, for unsupervised learning.

Utilize a content-based deep learning method and a collaborative filtration approach to develop recommender systems.

Develop a deep reinforcement learning model.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 21

Offered by: On Coursera provided by DeepLearning.AI

Duration: 27 hours (approximately)

Schedule: Flexible

Reviews for Unsupervised Learning, Recommenders, Reinforcement Learning

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Featured Tools

Machine Learning Accessible to All

ISO/IEC 42001: AI Management System

Beginners Guide to ChatGPT: AI for Market Research

Functions, Tools and Agents with LangChain

Alternative Tools for Unsupervised Learning, Recommenders, Reinforcement Learning

Legaliser is an AI-powered platform facilitating contract analysis and drafting for personal and business needs, featuring contract evaluation, fairness assessment, risk analysis, and anomaly identification.

#legal #contract analysis

Deep Learning for Computer Vision Specialization

Use AI skills to advance your engineering career. Acquire practical knowledge regarding deep learning methodologies for computer vision.

#Anomaly Detection #Artificial Intelligence (AI)

Foundations of Machine Learning

Develop and evaluate machine learning models using regression, trees, and unsupervised techniques to address various business challenges.

#Logistic Regression #Unsupervised Learning

ML Specialization

Specialization in Machine Learning at BreakIntoAI. Master the fundamental AI concepts and cultivate practical machine learning skills in the beginner-friendly, three-course program by AI visionary Andrew Ng.

#Logistic Regression #Artificial Neural Network

Machine Learning in Trading Specialization

Begin Your Career in Trading with Machine Learning. Familiarize yourself with the machine learning methodologies employed in quantitative trading.

#Learning Model Development #Algorithm Optimization

Machine Learning Intro to Everyone

The course's topics including the distinction between deep learning, machine learning, and artificial intelligence, the process of developing machine learning models, the difference between supervised and unsupervised learning, and the use of metrics for evaluating classification models.

#Artificial Intelligence (AI) #Reinforcement Learning

IBM Intro to ML Specialization

Acquire knowledge of machine learning by examining actual applications. Develop the necessary skills for a vocation in one of the most pertinent areas of contemporary AI by participating in hands-on projects and completing coursework from IBM's experts.

#Unsupervised Learning #Machine Learning

ML Theory & Hands-on: Python Specialization

Learn to develop, assess, and enhance machine learning models using Python libraries, covering introductory deep learning, supervised, and unsupervised learning algorithms.

#Unsupervised Learning #Python Programming

Reinforcement Learning Specialization

Gain a comprehensive understanding of the principles of reinforcement learning. Develop a comprehensive RL solution and comprehend the application of AI tools to address real-world issues.

#Function Approximation #Artificial Intelligence (AI)