Machine Learning courses

1656 Courses

Mejora tu negocio con Inteligencia Artificial

Este curso tiene la intención de servir como una guía esencial para emprendedores modernos, ayudando tanto en la creación de nuevos negocios como en la transformación de empresas existentes mediante la inteligencia artificial y las metodologías de innovación actuales. Ofrecido por el prestigioso Tecnológico de Monterrey, a través de Coursera, es.

AWS Skill Builder

Amazon SageMaker Getting Started

Welcome to "Amazon SageMaker Getting Started" course. Designed for individuals new to Amazon SageMaker AI, this course offers a comprehensive introduction to its benefits and technical concepts. You'll learn to navigate the AWS Management Console and use a Jupyter notebook instance for training and prediction with a machine learning model. C.

Udemy

Learn Machine Learning Course with Python A to Z

Enroll in the "Learn Machine Learning Course with Python A to Z" to develop a thorough understanding of machine learning principles and applications across different industries. Offered by Udemy, this course meticulously covers a wide range of machine learning concepts and algorithms, prominently featuring Python as the primary programming la.

Coursera

(KK) Generative AI with Large Language Models

Coursera Dive into the fundamentals of generative AI with our comprehensive course on Large Language Models (LLMs). This program is designed to equip learners with essential knowledge to deploy generative AI in practical scenarios. Understand the lifecycle of LLM-based generative AI and the key steps involved, including data gathering, model.

Udemy

Speech Recognition with Python

Unlock the potential of speech recognition technology by mastering it with Python. This comprehensive course provides an in-depth understanding, starting from fundamental principles to exploring cutting-edge AI applications. Offered by Udemy, a leader in online education, this course covers essential topics across multiple categories includin.

Udemy

Mastering ChatGPT Prompt Engineering: Beginner to Advanced

Udemy

30 Projects in 30 days of AI Development Bootcamp

Join our intensive 30 Projects in 30 Days of AI Development Bootcamp and gain unparalleled hands-on experience. Dive deep into the essential concepts and practical applications of Artificial Intelligence, Python, and related technologies. Build proficiency in machine learning, computer vision, deep learning, and neural networks using top frame.

Udemy

Master Python & Generative AI for Advanced Analytics

Udemy

Fast-Track Deep Learning: Master AI Foundations in 15 Days

Unlock the world of Artificial Intelligence with our intensive 15-day course, "Fast-Track Deep Learning: Master AI Foundations in 15 Days." Perfect for beginners, this program guides you from zero experience to building your very own AI models using PyTorch. Enroll today and expand your skill set in the rapidly growing fields of machine learn.

Udemy

AI for Business Leaders - AI Innovation in 10 Use Cases

Delve into the world of Artificial Intelligence with our comprehensive course, "AI for Business Leaders - AI Innovation in 10 Use Cases." This course is designed to empower business leaders to identify and harness the opportunities presented by Generative AI across various industries. Understand the risks involved and learn strategies to leve.

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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!