Managers have a key role to play to make Machine Learning (ML) work for any organization. This non-technical but practical workshop is the first to be designed for Managers with no prior knowledge of ML. It provides the missing piece to identify the best opportunities with Machine and Deep Learning (DL) technologies, to apply them in your own projects, and to generate business value from data.
PAPIs is the 1st series of international conferences dedicated to real-world Machine Learning applications, techniques, and tools. Previous editions took place in Boston, Sydney, Barcelona, Paris, Valencia, London, and PAPIs Latam will be held in São Paulo for the 3rd time! It will bring together engineers, scientists, researchers, hackers and managers who will meet to share experiences and discover the latest innovations, techniques, and tools to build ML applications.
This technical workshop for beginners in Deep Learning will teach you how single and multi-layered Neural Networks are trained on data. You’ll learn how to create, evaluate and optimize them with Keras. We’ll explain how Convolutional Neural Networks work, and we’ll use them to tackle an image classification challenge on Kaggle. Finally, we’ll introduce the concept of Transfer Learning, and we’ll put it to work on the same challenge, to speed up training and increase accuracy.
This course is part of UCL School of Management's MSc in Business Analytics. The module on Predictive Analytics builds on the foundational courses of this Masters to explore techniques from data mining, statistics, modelling and machine learning in greater detail. We will analyse current data to make predictions about future events across a variety industry use cases with support specific companies and practitioners.
In this workshop for developers, you'll gain an understanding of the possibilities and limitations of Machine Learning, and how to put it to work on real cases. You'll learn to prepare data, to create ML models, to evaluate them in your domain of application, to optimize them, and to deploy them. Adopt a top-down, results-first and experimentation-driven approach, and focus on practical techniques applied to concrete examples.
“The ML revolution depends on YOU”