Machine Learning courses

1334 Courses

LinkedIn Learning

Ya Xu: How to Turn AI from a Buzz Word to a Business Tool

Ya Xu: How to Turn AI from a Buzz Word to a Business Tool | LinkedIn Learning Ya Xu: How to Turn AI from a Buzz Word to a Business Tool Explore the opportunities and challenges presented by AI with Ya Xu, the head of data and AI at LinkedIn. This LinkedIn Learning course delves into practical approaches to integrating AI.

PyTorch for Deep Learning

PyTorch for Deep Learning Learn PyTorch and become a proficient Deep Learning Engineer. This PyTorch course is a step-by-step guide designed to help you develop your own deep learning models. The curriculum includes essential topics such as Computer Vision, Neural Networks, and much more.

ChatGPT and Large Language Models (LLMs): A Practical Guide

ChatGPT and Large Language Models (LLMs): A Practical Guide Learn how ChatGPT actually works! This course will get you up to speed on how LLMs work under the hood including topics like Prompt Design, Fine-Tuning, and more. Categories: Artificial Intelligence Courses, Machine Learning Courses, ChatGPT Courses, Fine-Tuning Courses

Introduction to ChatGPT Code Interpreter

Introduction to ChatGPT Code Interpreter Unlock the potential of ChatGPT's Code Interpreter tool in this concise course. Delve into aspects of data analysis and machine learning using practical, real-world data. Gain hands-on experience and enhance your coding skills with one of the most advanced AI tools available. Categories: Python Courses, M.

France Université Numerique

L'intelligence artificielle générative et moi

L'intelligence artificielle générative et moi Voici un mini MOOC pour vous former rapidement à l’IA générative dans votre quotidien. Il s’agira de comprendre comment elle transforme notre vie de tous les jours, nos métiers et nos compétences. Université: France Université Numerique Catégories: Cours d'Intelligence Artificielle, Cours de Machine.

Zero To Mastery

Artificial Intelligence in Cybersecurity

Artificial Intelligence in Cybersecurity | Zero To Mastery Dive into the vital intersection of artificial intelligence and cybersecurity with this comprehensive course. Understand the vulnerabilities and security challenges associated with Large Language Models (LLMs) and machine learning. Offered by Zero To Mastery University, this course is id.

Coursera

GenAI for Sales Teams

GenAI for Sales Teams Generative Artificial Intelligence (GenAI) is transforming the sales process, providing sales teams with innovative tools to enhance productivity, efficiency, and overall impact. By utilizing advanced language models and AI-driven capabilities, sales professionals can optimize workflows, tailor customer engagements, and gain.

Coursera

GenAI for DevOps Practitioners

As part of the GenAI Academy, "GenAI for DevOps Practitioners" is an in-depth course exploring the transformative effects of Generative Artificial Intelligence (GenAI) on DevOps. This primer helps learners discover key GenAI capabilities while providing practical strategies for adopting these powerful tools in everyday DevOps tasks. Through.

AWS Skill Builder

Developing Generative Artificial Intelligence Solutions (Vietnamese)

Developing Generative Artificial Intelligence Solutions (Vietnamese) Trong khóa học này, bạn sẽ khám phá vòng đời của ứng dụng trí tuệ nhân tạo tạo sinh (AI tạo sinh), bao gồm: Xác định trường hợp sử dụng trong kinh doanh Chọn mô hình nền tảng (FM) Cải thiện hiệu suất của FM Đánh giá hiệu suất của FM Triển khai và tác động của việc triể.

AWS Skill Builder

Exploring Artificial Intelligence Use Cases and Applications (Vietnamese)

Exploring Artificial Intelligence Use Cases and Applications (Vietnamese) Trong khóa học này, bạn sẽ khám phá các trường hợp sử dụng trí tuệ nhân tạo (AI), máy học (ML) và trí tuệ nhân tạo tạo sinh (AI tạo sinh) trong thực tế ở nhiều ngành khác nhau. Các lĩnh vực này bao gồm y tế, tài chính, tiếp thị, giải trí, v.v. Bạn cũng sẽ tìm hiểu về khả n.

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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!