Machine Learning courses

The course is devoted to the systematization of the mathematical background of the students necessary for the successful mastering of educational disciplines in the field of computer vision. The course includes sections of mathematical analysis,...

4.84

Participate in the application of machine learning, helping select between and evaluate technical approachesInterpret a predictive model for a manager or executive, explaining how it works and how well it predictsCircumvent the most common technical...

4.79

In this course, you will: - Explore the applications of GANs and examine them wrt data augmentation, privacy, and anonymity - Leverage the image-to-image translation framework and identify applications to modalities beyond images - Implement...

4.48

This is the sixth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow...

What's behind the machine learning hype? In this non-technical course, you’ll learn everything you’ve been too afraid to ask about machine learning. There’s no coding required. Hands-on exercises will help you get past the jargon...

Activities in these self-paced labs are derived from the exercises from the book Data Science on Google Cloud Platform by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this Google Cloud Labs Series, covering chapter...

Why Learn R? R is a widely used statistical programming language that’s beloved by users in academia and industry. R works well with data, making it a great language for anyone interested in data analysis,...

Tree-based machine learning models can reveal complex non-linear relationships in data and often dominate machine learning competitions. In this course, you'll use the tidymodels package to explore and build different tree-based models—from simple d...

3.88

It’s no secret that machine learning is one of the fastest-growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, Google Cloud has a...

4.64

This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised...

4.7

This course covers the theoretical foundation for different techniques associated with supervised machine learning models. In addition, a business case study is defined to guide participants through all steps of the analytical life cycle, from...

4.85

In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more....

4.47

>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area

4.57

This is the third course of the Advanced Machine Learning on GCP specialization. In this course,We will take a look at different strategies for building an image classifier using convolutional neural networks. We'll improve the...

4.57

This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You...

Train deep learning architectures such as Multi-layer perceptron, Convolutional Neural Networks and Recurrent Neural Networks for classificationValidate and compare different machine learning algorithmsPreprocess Electronic Health Records and represe...

4.68

Distinguish between artificial intelligence and data science concepts. Protect data privacy with ethical and legal standards. Assess the potential risks of bias. Advocate for the importance of risk evaluation in emerging technologies.

4.8

You will learn how to use the Azure Machine Learning Python SDK to create and manage enterprise-ready ML solutions.

4.36

The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering hidden structures...

4.75

This course introduces you to one of the main types of Machine Learning: Unsupervised Learning. You will learn how to find insights from data sets that do not have a target or labeled variable. You...