Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
Our Courses
Natural Language Processing with Sequence Models
In Course 3 of the Natural Language Processing Specialization, you will: a) Train a neural network with word embeddings to perform sentiment analysis of tweets, b) Generate synthetic Shakespeare text using a Gated Recurrent Unit (GRU) language model, c) Train a recurrent neural network to perform named entity recognition (NER) using LSTMs with linear layers, and d) Use so-called ‘Siamese’ LSTM models to compare questions in a corpus and identify those that are worded differently but have the same meaning. By the end of this Specialization, you will have designed NLP applications that perfo
-
Course by
-
Self Paced
-
24 hours
-
English
Device-based Models with TensorFlow Lite
Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. This second course teaches you how to run your machine learning models in mobile applications. You’ll learn how to prepare models for a lower-powered, battery-operated devices, then execute models on both Android and iOS platforms.
-
Course by
-
Self Paced
-
11 hours
-
English
Applied AI with DeepLearning
>>> 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
-
Course by
-
Self Paced
-
25 hours
-
English