Machine Learning courses

1795 Courses

FutureLearn

An Introduction to Artificial Intelligence in the Tourism Industry

An Introduction to Artificial Intelligence in the Tourism Industry delves into the transformative potential of AI and machine learning within the tourism sector. Amidst the background of the Fourth Industrial Revolution, this course, provided by FutureLearn and developed by the Luleå University of Technology, seeks to illuminate the profound change.

FutureLearn

On-Demand

Institut Mines-Télécom

Understanding Artificial Intelligence through Algorithmic Information Theory

Delve into the depths of Artificial Intelligence (AI) with the groundbreaking perspectives offered by Algorithmic Information Theory. This innovatively designed course unveils the essence of AI, beyond its complex problem-solving facade. Whether you're venturing into the realms of machine learning, keen on the nuances of reasoning, fascinated by th.

edX

On-Demand

FutureLearn

Artificial Intelligence and Machine Learning for Business

Title: Artificial Intelligence and Machine Learning for Business. Join us for an enlightening course that dives deep into how predictive analytics, fueled by machine learning and big data, can propel business success. In partnership with FutureLearn, this program demystifies the process of leveraging vast amounts of data to make informed decisions,.

FutureLearn

On-Demand

Politecnico di Milano

Technologies and platforms for Artificial Intelligence

Delve into the realm of Artificial Intelligence with this comprehensive course offered by Politecnico di Milano on Coursera. This detailed exploration covers the spectrum of hardware technologies essential for machine learning and deep learning, ranging from Internet-of-Things systems to expansive data centers. Furthermore, participants will gain i.

Coursera

On-Demand

Galileo University

Introducción a la Inteligencia Artificial: Principales Algoritmos

Descubre los fundamentos de la Inteligencia Artificial (IA) con el curso "Introducción a la Inteligencia Artificial: Principales Algoritmos", ofrecido por Galileo University en colaboración con edX. A lo largo de este curso, te sumergirás en los aspectos filosóficos y algorítmicos que rigen las técnicas de IA más empleadas hoy en día. El programa s.

edX

On-Demand

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Machine learning use cases

The use of machine learning has touched many areas in our lives. Let's look at the most striking examples of the use of computer intelligence:

Voice assistant Alisa. This system, without human help, will always find the answer to any question of interest, turn on music, answer the call and much more.

Selecting relevant advertising in browsers is not an easy process for a person, but it is quick for a computer. The system will analyze the viewing data and select what a particular user will like. The same system is used on various marketplaces - products that a person viewed or purchased are offered.

Chatbots in various dialogues. For example, many banks use bots to solve customer problems. It's convenient and fast.

Data security: Machine learning models can identify data security vulnerabilities before they become breaches. By analyzing past experiences, machine learning models can predict future high-risk actions so that risk can be mitigated proactively.

Finance: Banks, trading brokers and fintech firms use machine learning algorithms to automate trading and provide financial advisory services to investors. Bank of America uses chatbot Erica to automate customer support.

Healthcare: Machine learning is used to analyze massive medical data sets to speed up the discovery of treatments and cures, improve patient outcomes, and automate routine processes to prevent human errors. For example, IBM Watson uses data mining to provide doctors with data they can use to personalize patient care.

Fraud detection: AI is used in the finance and banking sector to autonomously analyze large numbers of transactions to identify fraudulent activities in real time. Technology services company Capgemini says fraud detection systems using machine learning and analytics reduce fraud investigation time by 70% and increase detection accuracy by 90% .

Retail: AI researchers and developers are using machine learning algorithms to develop AI recommendation engines that make relevant product suggestions based on shoppers' past choices, as well as historical, geographic and demographic data.

Facial recognition in the subway will help identify violators or criminals in a huge mass of people. Ordinary observers cannot cope with this task. But a fast-learning machine will do this job without any problems.

What do you need for machine learning (ML)?

For those interested in training, there are several requirements to be met in order to be successful in this field. So, there are the main points you need to know about the machine learning course. These requirements include:

Basic knowledge of programming languages such as Python, R, Java, JavaScript, etc.

Average knowledge of statistics and probability.

Basic knowledge of linear algebra in the ml course. In a linear regression model, a line is drawn through all the data points, and that line is used to calculate new values.

Understanding Calculus.

Knowledge of how to clean and structure raw data into the desired format to reduce the time required for decision making.

Machine learning courses from AI Eeducation are the best choice!