Home AI Courses Unsupervised Machine Learning

Unsupervised Machine Learning

(0 reviews)

Learn to implement and apply unsupervised learning techniques, focusing on clustering and dimension reduction algorithms, in a business environment.

Key AI Functions:Cluster Analysis,Dimensionality Reduction,Unsupervised Learning,Principal Component Analysis (PCA),K Means Clustering

Description

Reviews

Alternative Tools

Description for Unsupervised Machine Learning

Acquire knowledge of unsupervised learning, focusing on clustering and dimension reduction algorithms, and learn to select the appropriate algorithm for your data.

Explain problems suitable for unsupervised learning, describe the curse of dimensionality, and understand its challenges in clustering.

Define and implement common clustering and dimensionality-reduction algorithms, and compare per-cluster model performance.

Gain practical experience with optimal unsupervised learning strategies, comprehend relevant clustering metrics, and apply these techniques in a business environment.

Level: Intermediate

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by IBM

Duration: 23 hours (approximately)

Schedule: Flexible

Reviews for Unsupervised Machine Learning

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Featured Tools

AI & ML in Healthcare An Introduction

Exploratory Data Analysis for ML

Google Cloud Certification: Cloud Data Engineer Professional Certificate

ML con Spark (MLlib) en Databricks

Create Your First Chatbot with Rasa and Python

Alternative Tools for Unsupervised Machine Learning

Notably

Paid

Notably is an AI-driven research platform offering comprehensive features, including video transcription, sentiment analysis, and advanced search, to empower researchers across industries.

#research #transcription

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

Mathematics in ML Specialization

Machine learning mathematics. Find out about the mathematical prerequisites for applications in machine learning and data science.

#Eigenvalues And Eigenvectors #Principal Component Analysis (PCA)

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

ML: Concepts & Applications

Learn to use Python and libraries for data tasks, understand key machine learning techniques, and apply them to real-world datasets for a strong research foundation.

#Unsupervised Learning #Artificial Neural Network

Unsupervised Learning, Recommenders, Reinforcement Learning

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

#Anomaly Detection #Unsupervised Learning

ML in Mathematics: PCA

Apply mathematical concepts to real-world data, derive PCA from a projection perspective, comprehend orthogonal projections, and master Principal Component Analysis.

#Dimensionality Reduction #Python Programming

Interactive ML Dashboards using Plotly Dash

The course concentrates on the development of an HTML framework for a Plotly Dash dashboard that includes interactive scatter plots, bar charts, radio buttons, and dropdowns. It emphasizes the evaluation of model performance and the visualization of dimensionality reduction outcomes.

#Dimensionality Reduction #Machine Learning

Featured Tools

AI & ML in Healthcare An Introduction

Explore the intersection of healthcare, AI, and machine learning to acquire a deeper understanding of the practical applications and ethical implications of these technologies in enhancing patient care.

#artificial intelligence #machine learning

Exploratory Data Analysis for ML

Gain practical experience in AI and Machine Learning for business, focusing on data extraction, feature engineering, outlier management, and feature scaling for aspiring data scientists with foundational math and Python skills.

#Artificial Intelligence (AI) #Machine Learning

Google Cloud Certification: Cloud Data Engineer Professional Certificate

Investigate the objectives and advantages of Google's Big Data and Machine Learning products, including the use of BigQuery for interactive analysis, Cloud SQL, and Dataproc for migrating MySQL and Hadoop applications, and the selection of a variety of data processing tools on Google Cloud.

#Tensorflow #Bigquery

ML con Spark (MLlib) en Databricks

Learn to use Databricks and MLlib for creating and advancing machine learning models with Spark.

#Machine Learning #MLlib

Create Your First Chatbot with Rasa and Python

Learn the Rasa framework to create AI-powered chatbots, which is suitable for Python programmers who are new to chatbot development and lack prior machine learning experience. This course covers the fundamental components and practical applications.

#Chatterbot #Python Programming

Compare & Review AI Tool Directory AI Course Marketplace