Machine Learning courses

1336 Courses

LinkedIn Learning

Google Cloud Platform for Machine Learning Essential Training

Learn how to design machine learning solutions with Google Cloud Platform. Review services such as AutoML, CloudML Engine, and the GCP machine learning APIs.

LinkedIn Learning

Free Trial Available

2-3 hours

On-Demand

Udemy

Machine Learning Practical Workout | 8 Real-World Projects

Build 8 Practical Projects and Go from Zero to Hero in Deep/Machine Learning, Artificial Neural Networks

Udemy

Paid Course

14 hours 14 minutes

On-Demand

Udemy

Data Science: Deep Learning and Neural Networks in Python

The MOST in-depth look at neural network theory for machine learning, with both pure Python and Tensorflow code

Udemy

Paid Course

12 hours 7 minutes

On-Demand

Pluralsight

Getting Started with the Databricks Lakehouse Platform

This course will teach you how the Data Lakehouse architecture brings you the best of both Data Lakes and Data Warehouses allowing you to meet your data needs for big data processing, SQL analytics, and machine learning in a single platform.Organizations have long collected data in a variety of formats, structured, unstructured, and semi-structured.

Pluralsight

Free Trial Available

1 hour 39 minutes

On-Demand

LinkedIn Learning

Data Science and Analytics Career Paths and Certifications: First Steps

Learn about the history, roles, career paths, and industry-recognized certifications in the field of data science and analytics.

LinkedIn Learning

Free Trial Available

1-2 hours

On-Demand

Udemy

Time Series Analysis, Forecasting, and Machine Learning

Python for LSTMs, ARIMA, Deep Learning, AI, Support Vector Regression, +More Applied to Time Series Forecasting

Udemy

Paid Course

23 hours

On-Demand

Udemy

Machine Learning Made Easy : Beginner to Advanced using R

Learn Machine Learning Algorithms using R from experts with hands on examples and practice sessions. With 5 different pr

Udemy

Paid Course

15 hours

On-Demand

Udemy

Augmented Data Visualization with Machine Learning

Automated Analytics from Oracle Analytics Cloud and Machine Learning with Data Visualizations! Hands-on with Quizzes!

Udemy

Free Online Course

3 hours 15 minutes

On-Demand

Udemy

Fraud Analytics in Banking and Credit using Machine Learning

Understand fraud detection analytics and the robust internal controls and risk management system in organizations

Udemy

Paid Course

2-3 hours

On-Demand

Udemy

From 0 to 1: Machine Learning, NLP & Python-Cut to the Chase

A down-to-earth, shy but confident take on machine learning techniques that you can put to work today

Udemy

Paid Course

20 hours

On-Demand

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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!