Machine Learning courses

1335 Courses

Introduction to AI for Cybersecurity

Introduction to AI for Cybersecurity "Introduction to AI for Cybersecurity" offers you a comprehensive understanding of how artificial intelligence (AI) is revolutionizing the field of cybersecurity. This course provides an in-depth look at key AI techniques and their applications in bolstering security measures, threat detection, and the safeguar.

Coursera

Innovating with Google Cloud Artificial Intelligence - Español

Innovating with Google Cloud Artificial Intelligence - Español La inteligencia artificial (IA) y el aprendizaje automático (AA) representan una evolución importante en las tecnologías de la información que están transformando rápidamente una amplia variedad de sectores. En el curso “Innovating with Google Cloud Artificial Intelligen.

Pluralsight

AWS Maching Learning and Artificial Intelligence Fundamentals

AWS Machine Learning and Artificial Intelligence Fundamentals Artificial intelligence (AI) and machine learning (ML) are two of the most transformative technologies driving innovation today. This course will teach you the essentials of AI and ML. You probably already know that artificial intelligence (AI) and machine learning (ML) are at the f.

Johns Hopkins University

Artificial Intelligence in Social Media Analytics

Artificial Intelligence in Social Media Analytics | Johns Hopkins University | Coursera In the course "Artificial Intelligence in Social Media Analytics", learners will explore the intersection of artificial intelligence and social media analytics, equipping them with essential skills to navigate and analyze digital landscapes. By delving into m.

Coursera

Intro to Artificial Intelligence on Microsoft Azure

Intro to Artificial Intelligence on Microsoft Azure Whether you're just beginning to work with Artificial Intelligence (AI) or you already have AI experience and are new to Microsoft Azure, this course provides you with everything you need to get started. Artificial Intelligence (AI) empowers amazing new solutions and experiences; and Microsoft Az.

AWS Skill Builder

AWS Flash - Automating with AI/ML for Small Business Owners

AWS Flash - Automating with AI/ML for Small Business Owners This course provides small business owners with a high-level overview of generative artificial intelligence (AI). Learners will explore the basics of generative AI technology and how to implement it to help their business expand into new markets, increase customer satisfaction, and enable.

Johns Hopkins University

Social Media Analytics

Social Media Analytics This specialization is designed for post-graduate students aiming to develop advanced skills in social media analytics and its practical applications. Through four comprehensive courses, learners will explore key topics such as machine learning, natural language processing, sentiment analysis, and network analysis, equippin.

Johns Hopkins University

Advanced Methods in Machine Learning Applications

Advanced Methods in Machine Learning Applications The course "Advanced Methods in Machine Learning Applications" delves into sophisticated machine learning techniques, offering learners an in-depth understanding of ensemble learning, regression analysis, unsupervised learning, and reinforcement learning. Emphasizing practical application, this cou.

Wolfram U

What Is ChatGPT Doing ... and Why Does It Work?: Daily Study Group

What Is ChatGPT Doing ... and Why Does It Work?: Daily Study Group Find out what's going on inside ChatGPT and explore why it can perform so well at producing meaningful text. This Study Group is based on a best-selling book by Stephen Wolfram and provides an accessible and engaging explanation for the success of ChatGPT.

Wolfram U

Machine Learning Proficiency: Wolfram U Instructor-Led Course

Machine Learning Proficiency: Wolfram U Instructor-Led Course This instructor-led course provides an introduction to machine learning, neural networks, and LLMs, followed by hands-on projects using Wolfram technology. Learn how to build, train, and test models in this comprehensive, three-part course sequence that leverage.

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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!