Machine Learning

Learn how to deploy deep learning models on mobile and embedded devices with TensorFlow Lite. This course was developed by the TensorFlow team and Udacity as a practical approach to model deployment for software developers.

Welcome to Recommendation Systems! We've designed this course to expand your knowledge of recommendation systems and explain different models used in recommendation, including matrix factorization and deep neural networks.

In this course, you'll define clustering for ML applications, prepare data for clustering, define similarity for your dataset,  compare manual and supervised similarity measures, use the k-means algorithm to cluster data, evaluate the quality of your clustering result.

Learn how to build deep learning applications with TensorFlow. This course was developed by the TensorFlow team and Udacity as a practical approach to deep learning for software developers.

Discover some of the ways machine learning is helping improve lives and grow businesses with this free online course from Google.

By the end of this course, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot!

By the end of this Specialization, learners will understand the foundations of much of modern probabilistic AI and be prepared to take more advanced courses, or to apply AI tools and ideas to real-world problems.

In this course, you will learn the foundations of deep learning. This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications.

In this course, you'll build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.

This free, two-hour deep learning course provides an interactive introduction to practical deep learning methods. You will learn to use deep learning techniques in MATLAB® for image recognition.

The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods.

In this free TensorFlow course, you will be able to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions.