Machine Learning courses

1656 Courses

Udemy

XAI: Explainable AI

XAI: Explainable AI - Understanding Machine Learning Models in Python | Udemy Discover the secrets to demystifying machine learning models with our comprehensive course on Explainable AI. Designed for both beginners and seasoned data scientists, this Udemy course will guide you through the nuances of explainable artificial intelligence using Pyt.

Udemy

Neural Networks in Python from Scratch: Complete guide

Embark on a complete journey to understand neural networks with our course "Neural Networks in Python from Scratch." Dive into the world of Deep Learning, learning to build neural networks with Python from the ground up. Gain insights into both theory and hands-on practice, providing you with a robust understanding of deep learning methodol.

Udemy

Technology and Innovation for Legal Professionals

Are you a legal professional looking to stay ahead in the rapidly evolving legal landscape? Enroll in "Technology and Innovation for Legal Professionals" and transform your skillset. Offered by Udemy, this course is designed to provide you with essential tech knowledge. Immerse yourself in the world of Artificial Intelligence, Machine Learni.

Udemy

Causal Data Science with Directed Acyclic Graphs

Delve into the world of causal data science with a focus on directed acyclic graphs (DAGs). This comprehensive course equips you with modern tools essential for causal inference in the realms of machine learning and AI. Discover a multitude of practical examples utilizing R, enhancing both your theoretical understanding and practical skills. O.

Udemy

The Grey Wolf Optimizer

Unlock the fascinating world of optimization with "The Grey Wolf Optimizer" course. Designed to elevate your understanding and proficiency, this Udemy course delves into the inspirations and theories behind the Grey Wolf Optimizer. Enhance your capability in mathematical modeling and practical applications as you navigate through the comprehe.

Udemy

Machine Learning Product Management: A Practical Guide

Embark on a dynamic career path in Machine Learning Product Management with our dedicated course on Udemy. This practical guide is designed to equip you with essential skills to excel in fields such as Artificial Intelligence, Data Science, and Product Management. Delve into specialized areas including Data Transformation, Model Evaluation, M.

Udemy

How to easily use ANN for prediction mapping using GIS data?

Unlock the power of Artificial Neural Networks (ANNs) for Geographical Information Systems (GIS) with this comprehensive Udemy course. You'll learn how to leverage R programming to create effective prediction mapping using GIS data. This course, designed for enthusiasts and professionals alike, offers a simplified step-by-step methodology tha.

Udemy

How To Build AI / Machine Learning Startups | Sramana Mitra

Delve into the dynamic world of Artificial Intelligence and Machine Learning startups with expert guidance from Sramana Mitra. This course provides invaluable insights through case studies and showcases innovation and practical lessons from the forefront of AI and ML ventures. Available on Udemy, this learning experience is perfect for aspirin.

Udemy

Introduction to Artificial Neural Network and Deep Learning

Unlock the potential of artificial neural networks and deep learning with our comprehensive course on Udemy. Delve into the best machine learning techniques specifically tailored for data science, with practical applications in image recognition using Java and the Neuroph framework. Perfect for aspiring data scientists and developers eager t.

Coursera

GenAI for Financial Data Analysis

Dive into the world of Generative AI (GEN AI) and its remarkable impact on financial data analysis. This course offers hands-on exploration into how AI tools such as Microsoft Co-Pilot, ChatGPT, Datarobot, and Chartpixel are revolutionizing financial analytics. Designed for those with a foundational understanding of financial data and AI, t.

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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!