This is the code repository for Hands-On Unsupervised Learning with TensorFlow 2.0, published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Nowadays, machine learning is becoming increasingly important to businesses. It is used to solve various business problems using supervised and unsupervised algorithms. In unsupervised learning, Artificial Intelligence systems try to categorize unlabeled and unsorted data based on the similarities and differences that exist among data. In this case, the capabilities of unsupervised learning methods to generate a model based on data make it possible to deal with complex and more difficult problems in comparison with the capabilities of supervised learning. In this course, we examine different unsupervised learning methods and solve practical problems using the TensorFlow platform. Solving examples of real-world problems using TensorFlow is more inspiring and compelling and will enhance your practical skills. By the end of this course, you will gain significant hands-on experience using unsupervised learning algorithms with TensorFlow and will be able to make your own model to solve relevant real-world learning problems.
- The fundamentals of unsupervised learning algorithms and their importance
- TensorFlow 2.0 terminology
- Hands-on experience solving real-world problems in unsupervised learning
- A practical approach to solving business problems, ranging from data preprocessing to model-building from a given dataset
This course targets aspiring data scientists, data analysts, machine learning engineers, and more. Although the only requirement is a basic knowledge of programming with Python, overall knowledge of machine learning and supervised learning will help you (but isn't mandatory) acquire new skills in unsupervised learning algorithms. This course will facilitate your understanding of the intricacies of each model and how to code it. This course will help project managers, business analysts, and team leaders learn which unsupervised learning model to use for a specific business problem. It will also help people who are trying to build a career in Artificial Intelligence, data science, and machine learning understand models and their applications.
This course has the following requirements:
OS: Mac/Linux Ubuntu / Windows 10
Browser: Google Chrome, Internet Explorer
Anaconda and Google Colab
Prior average knowledge in programming with Python
Overall knowledge about Machine Learning and Supervised learning is essential