35 TensorFlow courses in Glasgow delivered On Demand

In this self-paced course, you will learn how to use TensorFlow 2 to build deep neural networks. You will learn the basics of machine learning, classification, and regression. We will also discuss the connection between artificial and biological neural networks and how that inspires our thinking in deep learning.

In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks (RNNs). You will learn about sequence data, forecasting, Elman Unit, GRU, and LSTM. You will also learn how to work with image classification and how to get stock return predictions using LSTMs. We will also cover Natural Language Processing (NLP) and learn about text preprocessing and classification.

In this self-paced course, you will learn how to use TensorFlow 2 to build convolutional neural networks (CNNs). You will learn how to apply CNNs to several practical image recognition datasets and learn about techniques that help improve performance, such as batch normalization, data augmentation, and transfer learning.

This comprehensive course will help you learn how to use the power of Python to evaluate your deep learning-based recommender system data sets based on user ratings and choices with a practical approach to building a deep learning-based recommender system by adopting a retrieval-based approach based on a two-tower model.

This course starts with the basics of Recurrent Neural Networks (RNNs) with Python and then teaches you how to build them by taking you through various exercises and projects. You will be able to test your skills by completing two exciting projects: creating an automatic book writer and a stock price prediction application.

Kickstart your journey into deep learning and gain a strong understanding of deep neural networks through practical exercises. Develop your intuition and learn the fundamentals of artificial neural networks, activation functions, and loss functions. Gain practical experience with Python and TensorFlow 2.x, and apply your skills to build powerful deep learning models.

Are you fascinated with Netflix and YouTube recommendations and how they accurately recommend content that you would like to watch? Are you looking for a practical course that will teach you how to build intelligent recommendation systems? This course will show you how to build accurate recommendation systems in Python using real-world examples.

This course is your guide to deep learning in Python with Keras. You will discover the Keras Python library for deep learning and learn how to use it to develop and evaluate deep learning models.

Get started with Neural networks and understand the underlying concepts of Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks. This hands-on course will help you understand deep learning in detail with no prior coding or programming experience required.

This comprehensive deep learning course with Python will start with the basics and work up to advanced topics such as using different frameworks in Python to solve real-world problems and building artificial neural networks with TensorFlow and Keras.