Machine Learning courses

1656 Courses

Udemy

The Complete Intro to Machine Learning

Udemy

Complete Python and Machine Learning in Financial Analysis

Udemy offers an extensive course titled "Complete Python and Machine Learning in Financial Analysis" that combines practical use of Python with advanced Machine Learning and Deep Learning methods tailored for financial analytics. This course is structured with step-by-step coding instructions alongside all required codes, enhancing your skills i.

Udemy

AWS SageMaker Practical for Beginners | Build 6 Projects

Embark on your machine learning journey with our beginner-friendly course on AWS SageMaker, designed to equip you with hands-on experience in building real-world projects. This comprehensive Udemy course covers essential algorithms such as Linear Learner, XGBoost, and PCA, alongside Image Classification techniques. Dive deep into the world of.

Udemy

Decision Trees, Random Forests, AdaBoost & XGBoost in Python

Join our comprehensive course on Udemy to master Decision Trees and Ensembling techniques using Python. Delve into the world of machine learning and data analysis as you learn to implement Bagging, Random Forest, Gradient Boosting Machine (GBM), AdaBoost, and XGBoost efficiently. Perfect for data enthusiasts aiming to enhance their skills in.

Udemy

Complete Machine Learning & Data Science with Python| ML A-Z

Embark on a comprehensive journey into the world of Machine Learning and Data Science with Python. This course offers in-depth knowledge of tools like Numpy, Pandas, Matplotlib, Seaborn, and Scipy. Through this course, offered by Udemy, participants will gain practical insights into supervised and unsupervised machine learning techniques, along.

Udemy

Machine Learning: Master the Fundamentals

Discover the essentials of machine learning with Udemy's comprehensive course, "Machine Learning: Master the Fundamentals." This online course guides you through the intricacies of Python programming, Natural Language Processing (NLP), and Deep Learning techniques. Whether you're a beginner or looking to upgrade your skills, this course provi.

Udemy

Master in Data Science, Data Analytics and Data Analysis

Master in Data Science, Data Analytics, and Data Analysis | Udemy Boost your skills with the Master in Data Science, Data Analytics, and Data Analysis course available on Udemy. Dive into advanced topics such as Machine Learning, Artificial Intelligence, and Generative AI using popular programming languages like Python and R. Gain valuable.

Udemy

Linear Regression and Logistic Regression in Python

Discover the fundamentals of Linear Regression and Logistic Regression with this beginner-friendly course on Udemy. Designed for those with no prior experience in coding or mathematics, you'll learn to build predictive machine learning models efficiently and effectively. This course is part of Udemy's diverse offerings in Python, Machine Learni.

Udemy

Logistic Regression in Python

Logistic Regression in Python | Beginner's Tutorial | Udemy Take your first steps in mastering logistic regression with our Python tutorial tailored for beginners. This course will equip you with the foundational skills required for effective predictive modeling using Python. By the end, you'll be ready to tackle complex data analysis tasks with.

Udemy

ML for Business Managers: Build Regression model in R Studio

Master the fundamentals of Simple and Multiple Regression, crucial components of Machine Learning and Econometrics, by building a Regression model using R Studio. This course, offered by Udemy, provides a comprehensive introduction to Linear Regression, equipping Business Managers and aspiring data scientists with the skills necessary 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!