Machine Learning courses

1003 Courses

2022 Complete Data Structures: Data Structures With Python

Embark on a comprehensive journey through data structures with the 2022 Complete Data Structures: Data Structures With Python course. Perfect for absolute beginners and seasoned developers alike, this course will guide you through the essentials of Python and the implementation of various data structures, enhancing your skills to build advance.

Her Seviyeye Uygun Uçtan Uca Veri Bilimi, Knime ile

Her Seviyeye Uygun Uçtan Uca Veri Bilimi, Knime ile En çok aranan niteliklerden olan veri bilimi, yapay zeka, büyük veri ve veri analizi konularına giriş eğitimi. Categories: Artificial Intelligence Courses Machine Learning Courses Data Analysis Courses Marketing Courses.

Google Cloud Digital Leader Training 日本語版

Google Cloud Digital Leader Training 日本語版 Cloud Digital Leader トレーニングは、クラウドリテラシー、一般的なビジネスユースケース、クラウドソリューションと Google Cloud コア製品の機能が、企業をどのようにサポートするかについて個々の実務家またはチーム全体をスキルアップするように設計された 4 つのコースで構成されています。このトレーニングは、.

Create Voice Controlled AR Apps 1: Build a Car Showcase Application

Create Voice Controlled AR Apps 1: Build a Car Showcase Application Take this project-based course and learn how to create immersive, commercially viable augmented reality (AR) apps that can be controlled with voice commands, using Vuforia and Unity.

Become a Machine Learning Specialist

Are you ready to take a deeper dive into mastering the concepts and techniques involved in machine learning? This learning path shows how machine learning algorithms work and how to design them yourself. There's a lot to learn in this rapidly growing (and highly recruited-for) field, and these courses will give you an extremely solid skill set.

Machine Learning & AI Foundations: Linear Regression

Machine Learning & AI Foundations: Linear Regression Expand your data science skills by learning how to leverage the concepts of linear regression to solve real-world problems. Categories: Artificial Intelligence Courses, Machine Learning Courses, Data Science Courses, Linear Regression Courses

Building a Recommendation System with Python Machine Learning & AI

Discover how to use Python to build programs that can make recommendations. This hands-on course explores different types of recommendation systems and shows how to build each one. Categories: Artificial Intelligence Courses, Python Courses, Machine Learning Courses, Programming Courses, Recommender Systems Courses.

Digital Transformation Tips

Digital Transformation Tips Learn how to best support the digital transformation efforts of your business. Get actionable tips for leveraging technology and planning for success. Categories: Artificial Intelligence Courses Machine Learning Courses Big Data Courses Digital Transformation Courses Cloud Computing Courses Internet of T.

Machine Learning and AI Foundations: Causal Inference and Modeling

Machine Learning and AI Foundations: Causal Inference and Modeling Enroll in our comprehensive course, "Machine Learning and AI Foundations: Causal Inference and Modeling," and delve into the essential modeling techniques and experimental designs that are crucial for establishing causal inference. Enhance your understanding and.

DJ Patil: Ask Me Anything

DJ Patil: Ask Me Anything Join former U.S. chief data scientist DJ Patil as he tackles questions posed by LinkedIn members. Topics range from data security to the future of data science. Categories: Artificial Intelligence Courses Machine Learning Courses Neural Networks Courses Data Science Courses Internet of Things Courses Cyber.

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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!