In this class you will learn the basic principles and tools used to process images and videos, and how to apply them in solving practical problems of commercial and scientific interests. Digital images and videos are everywhere these days – in thousands of scientific (e.g., astronomical, bio-medical), consumer, industrial, and artistic applications. Moreover they come in a … [Read more...] about Fundamentals of Digital Image and Video Processing
Algorithms
Deep Neural Networks with PyTorch
The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation … [Read more...] about Deep Neural Networks with PyTorch
Introduction to battery-management systems
This course can also be taken for academic credit as ECEA 5730, part of CU Boulder’s Master of Science in Electrical Engineering degree. This course will provide you with a firm foundation in lithium-ion cell terminology and function and in battery-management-system requirements as needed by the remainder of the specialization. After completing this course, you will be able … [Read more...] about Introduction to battery-management systems
Sequence Models
In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and … [Read more...] about Sequence Models
Natural Language Processing with Classification and Vector Spaces
In Course 1 of the Natural Language Processing Specialization, you will: a) Perform sentiment analysis of tweets using logistic regression and then naïve Bayes, b) Use vector space models to discover relationships between words and use PCA to reduce the dimensionality of the vector space and visualize those relationships, and c) Write a simple English to French translation … [Read more...] about Natural Language Processing with Classification and Vector Spaces
