Machine Learning courses

1335 Courses

LinkedIn Learning

AI and the Future of Work: Workflows and Modern Tools for Tech Leaders

AI and the Future of Work: Workflows and Modern Tools for Tech Leaders Explore the integration of machine learning operations in your business. Unveil the potential of machine learning and navigate through its challenges. This comprehensive course offered by LinkedIn Learning will equip tech leaders with the skills to harness modern tools and wo.

LinkedIn Learning

Introduction to AI-Native Vector Databases

Introduction to AI-Native Vector Databases | LinkedIn Learning Discover how to enhance data systems using artificial intelligence with LinkedIn Learning's course, "Introduction to AI-Native Vector Databases." This course is tailored for data and AI professionals keen on optimizing their data storage and retrieval processes through adva.

AWS Skill Builder

Digital Classroom - Generative AI for Executives

Digital Classroom - Generative AI for Executives Generative AI for Executives will teach you how to leverage the power of generative AI to drive real business value. You'll start by recognizing the potential of these new AI technologies and identifying specific use cases you can implement right away. From there, you'll cover best practices for usi.

LinkedIn Learning

Advanced Python Projects: Build AI Applications

LinkedIn Learning

AI and Machine Learning Tools for After Effects

AI and Machine Learning Tools for After Effects - LinkedIn Learning Unlock the potential of AI and machine learning tools in Adobe After Effects with this expertly designed course from LinkedIn Learning. Dive deep into the integration and application of advanced technologies to enhance your video editing and animation projects. Categ.

AWS Skill Builder

Exam Prep Official Practice Question Set: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)

Exam Prep Official Practice Question Set: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) The Exam Prep Official Practice Question Set: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) includes 20 questions. This question set aligns with the MLA-C01 version of the exam and exam guide. Official practi.

AWS Skill Builder

Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)

Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) The Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) includes 65 questions and has a time limit of 130 minutes. This pretest aligns with the MLA-C01 version of the exam and exam guide. About AWS Ce.

AWS Skill Builder

Exam Prep Official Pretest: AWS Certified AI Practitioner (AIF-C01 - English)

Exam Prep Official Pretest: AWS Certified AI Practitioner (AIF-C01 - English) The Exam Prep Official Pretest: AWS Certified AI Practitioner (AIF-C01 - English) includes 65 questions and has a time limit of 90 minutes. This pretest aligns with the AIF-C01 version of the exam and exam guide. About AWS Certification Exam Prep Official Pretests Gain c.

openSAP

Building AI and Sustainability Solutions on SAP BTP

Building AI and Sustainability Solutions on SAP BTP This course explores how SAP is taking action on sustainability goals and enabling customers to become intelligent, sustainable enterprises. SAP Business Technology Platform provides a foundation for application development, integration, data, analytics, and AI. SAP has also developed a sustain.

LinkedIn Learning

Exploring AIOps

Exploring AIOps Discover how the exciting new world of AIOps is transforming everyday IT workflows and practices globally. Join this comprehensive course offered by LinkedIn Learning and stay ahead in the evolving field of Artificial Intelligence. Categories: Artificial Intelligence Courses, Machine Learning Courses, Predictive Analytics Course.

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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!