Introduction to Deep Learning Business Applications for Developers

Covers the latest developments in Deep Learning and offers concrete advice on how to implement Deep Learning in your business Explains the complexities in deploying a Deep Learning platform in-house or on the cloud integrating with Data Warehouse Discusses concrete implications of Deep Learning in many business areas, from conversational bots in customer service to medical image processing

Autorentext
Dr Armando Vieira is a Data Scientist and Artificial Intelligence consultant with an entrepreneurial mindset. Passionate about how to make Machine Learning projects work for organizations and how to build great AI based products.As algorithms are becoming a commodity, the challenge is not building them but using them to solve real problems.
Have coordinated several projects on Credit Risk Evaluation, Recommendation Systems, Clustering Analysis and Predictive Analytics.

Bernardete Ribeiro is Professor at University of Coimbra, Portugal. She has a Ph.D. and Habilitation in Informatics Engineering. She is Director of the Center of Informatics and Systems of the University of Coimbra (CISUC).She is President of the Portuguese Association of Pattern Recognition (APRP). She is Founder and Director of the Laboratory of Artificial Neural Networks (LARN) for more than 20 years. She is IEEE SMC Senior member, member of International Association of Pattern Recognition (IAPR), International Neural Network Society (INNS), and ACM. Her research interests are in the areas of Machine Learning, Pattern Recognition, and their applications to abroad range of fields. She is author or co-author of over three hundred publications including books, journalsand international and national conferences. She has delivered numerous invited talks, seminars, and short courses.

Inhalt
1 Introduction.- 2 Deep Learning: An Overview.- 3 Deep Neural Network Models.- 4 Image Processing.- 5 Natural Language Processing and Speech.- 6 Reinforcement Learning and Robotics.- 7 Recommendations Algorithms and Advertising.- 8 Games and Art.- 9 Other Applications.- 10 Business Impact of DL Technology.- 11 New Research and Future Directions.- Appendix Training DNN with Keras.