Machine Learning courses

1656 Courses

Udemy

Machine Learning with TensorFlow on Google Cloud

Discover the world of machine learning with our in-depth course on using TensorFlow on Google Cloud. This hands-on experience allows you to build, train, and deploy robust ML models utilizing Google's powerful infrastructure. Whether you're delving into neural networks or mastering regression techniques, this course offers a comprehensive gui.

Udemy

Become a TensorFlow Certified Professional Developer

Elevate your AI expertise with our immersive training program designed to prepare you as a TensorFlow Certified Developer. Offered by Udemy, this course provides an unparalleled opportunity to sharpen your skills in various key AI domains. Whether you're delving into Machine Learning, diving deep into Neural Networks, or exploring the intricac.

Udemy

Machine Learning Project: Heart Attack Prediction Analysis

Udemy

MLOps with AWS - Bootcamp - Zero to Hero Series

MLOps with AWS - Bootcamp - Zero to Hero Series Embark on your path to mastering MLOps with our comprehensive AWS bootcamp. This course is designed to elevate your skill set from fundamental notebook development to advanced production operations using AWS's powerful suite of AI and ML tools. Led by industry experts, the bootcamp provides a gui.

Udemy

Complete PySpark & Google Colab Primer For Data Science

Master the art of building machine learning and neural network models using PySpark and Google Colab with this comprehensive primer. Perfectly suited for aspiring data scientists, this Udemy course covers essential topics including machine learning, big data, deep learning, and more. Discover how to efficiently process data and perform stati.

Udemy

Machine Learning for Interviews & Research and DL basics

Udemy

Machine Learning for Data Analysis: Unsupervised Learning

Unlock the power of Machine Learning for Data Analysis with a focus on Unsupervised Learning. This course is designed to bring complex concepts into the realm of simplicity using Excel. Dive into sophisticated topics that enhance your data analysis and business intelligence capabilities. Brought to you by Udemy, this course belongs to a robust.

Udemy

Microsoft Fabric - The Complete Guide

Explore the in-depth journey to mastering Microsoft Fabric through this all-inclusive guide designed to take you from foundational concepts to advanced expertise. Offered to you by Udemy, this course provides a thorough understanding of Microsoft Fabric, integrating critical insights into data science, machine learning, data warehousing, dat.

Udemy

End to End Data Science Practicum with Knime

Embark on an informative journey into the world of data science with our "End to End Data Science Practicum with Knime" offered by Udemy. This course empowers you to master key data science concepts and techniques using Knime, supported by practical hands-on examples. Whether your interest lies in data visualization, regression analysis, clust.

Udemy

Machine Learning & Data Science: The Complete Visual Guide

Visit Course on Udemy Delve into the world of machine learning and data science with our comprehensive visual guide. This course offers an easy-to-follow approach with straightforward demos and Excel models, ensuring a complete understanding without the need for programming skills. Ideal for beginners and those seeking a practical, visual lear.

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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!