Machine Learning courses

1336 Courses

Udemy

Pomodoro ile 1 Haftada Python Ögrenin + 100 Soru-Çözüm

Pomodoro ile 1 Haftada Python Öğrenin + 100 Soru-Çözüm Kısa sürede Python'un tüm detaylarını öğrenebilirsiniz. Ayrıca bilginizi ödev, quiz ve kodlama egzersizleri ile pekiştirin. Bu kurs, Python bilgilerinizi 100 soru-çözüm ile test etme ve geliştirme fırsatı sunar. Sağlayıcı: Udemy Kategori: Robotik Kursları, Yapay Zeka Kursları, Python Kurslar.

Udemy

Paid Course

20 hours 38 minutes

On-Demand

Coursera

The Art & Science of Product Management

The Art & Science of Product Management Sponsored by AMAZON WEB SERVICES (AWS) Learn how Amazon, Facebook, Google, and Twitch PMs lead and collaborate with an interdisciplinary team of UX designers, software engineers, and AI/ML engineers. Plus, practice real PM interview questions asked by Microsoft, Google, and Amazon! Featuring: NANCY.

Coursera

Free Online Course (Audit)

9-10 hours

On-Demand

University of Virginia

Product Analytics and AI

Product Analytics and AI - University of Virginia | Coursera Few capabilities focus agile like a strong analytics program. Such a program determines where a team should focus from one agile iteration (sprint) to the next. Successful analytics are rarely hard to understand and are often startling in their clarity. In this course, developed at th.

Coursera

Free Online Course (Audit)

15 hours

On-Demand

Coursera  Specialization

Advanced Data Science with IBM

Advanced Data Science with IBM As a Coursera certified specialization completer, you will demonstrate a deep understanding of massive parallel data processing, data exploration and visualization, along with advanced machine learning and deep learning. You will grasp the mathematical foundations behind all machine learning and deep learning algori.

Coursera  Specialization

Paid Course

17 weeks, 5 hours a week

Coursera  Professional Certificate

Preparing for Google Cloud Certification: Cloud Data Engineer

Preparing for Google Cloud Certification: Cloud Data Engineer Google Cloud Professional Data Engineer certification was ranked #1 on Global Knowledge's list of 15 top-paying certifications in 2021! Enroll now to prepare! 87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to a.

Coursera  Professional Certificate

Paid Course

22 weeks, 3 hours a week

Udemy

Full stack web development and AI with Python (Django)

Full Stack Web Development and AI with Python (Django) | Udemy

Udemy

Paid Course

40 hours

On-Demand

Deep-Dive into Tensorflow Activation Functions

Deep-Dive into Tensorflow Activation Functions You've learned how to use Tensorflow. You've learned the important functions, how to design and implement sequential and functional models, and have completed several test projects. What's next? It's time to take a deep dive into activation functions, the essential function of every node and layer o.

Deep Learning with TensorFlow 2.0

Deep Learning with TensorFlow 2.0 Embark on a transformative journey into the realm of deep learning by leveraging TensorFlow 2.0. This course is designed to equip you with the skills needed to build cutting-edge deep learning algorithms, dive deep into the intricacies of neural networks, and apply this knowledge effectivel.

Machine Learning for Apps

Machine Learning for Apps Start building more intelligent apps with Machine Learning. Take advantage of this new foundational framework! Artificial Intelligence Courses Machine Learning Courses Neural Networks Courses Core ML Courses

Data Engineering und Data Science – Klarheit in den Schlagwort-Dschungel

Data Engineering und Data Science – Klarheit in den Schlagwort-Dschungel Die Schlagwörter Künstliche Intelligenz, Data Science, Data Engineering, und Big Data dominieren seit einigen Jahren nicht nur die IT-Schlagzeilen. In unserem Kurs wollen wir diese Wörter mit grundlegendem Inhalt füllen und die typischen Arbeitsschritte eines Data Scientists.

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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!