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Course Outline
Introduction to Deep Learning
- Impact on the Medical Industry
- Successes and Failures in Deep Learning in Various Industries
Understanding Deep Learning
- Artificial Intelligence and Machine Learning
- Basic Concepts of Deep Learning
- Applications for Deep Learning
- The role of Big Data in Deep Learning
Overview of Common Deep Learning Techniques
- Neural Networks
- Natural Language Processing
- Image Recognition
- Speech Recognition
- Sentiment Analysis
Applying Deep Learning Techniques to Issues in Medicine
- Exploring the Opportunities for Improvement in the Medical Field
- Examining the Applicability of Deep Learning Techniques to the Cited Issues
Exploring Deep Learning Case Studies for Medicine
- DeepVentricle Algorithm for Ventricular Segmentation in Cardiac MR by Arterys
- Skin Cancer Diagnosis Algorithm by Stanford
- Heart Failure Prediction Algorithm by Sutter Health and the Georgia Institute of Technology
- Radiology Scans Diagnoses Across All Modalities by Behold.AI
- Clinical Decision Support Technologies by Enlitic
- Personalized Medicine and Therapies by Deep Genomics
- Decoding Cancer with Freenome
- Detection of Diabetic Retinopathy by Google
- Chatbot for Prevention and Diagnosis of Disease by Babylon Health
Limitations of Deep Learning
Ethical Implications and Data Privacy Concerns in Deep Learning
Creating New Business Models Based on Deep Learning-Enabled Platforms and Ecosystems
Bringing it All Together
- Choosing Deep Learning Solutions that Fit Your Needs
- Strategies for Adoption of Deep Learning Technologies
Team Communication and Managerial Buy-In
- Conversations with Managers and Leaders
- Conversations with Engineers and Data Scientists
Summary and Conclusion
Requirements
- Experience in the medical industry
- No programming experience is required
Testimonials
Abhi always made sure we were following along. Good mix of practice and theory.
Margaret Elizabeth Webb, Department of Jobs, Regions, and Precincts
Deep Reinforcement Learning with Python Course
The Colab Notebooks with the training and examples notes.
Felix Navarro, Motorola Solutions
Deep Learning for Telecom (with Python) Course
The exercises were very good and interactive. Instructors were always answering all questions and providing their insight on all topics
Felix Navarro, Motorola Solutions
Deep Learning for Telecom (with Python) Course
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Margaret Elizabeth Webb, Department of Jobs, Regions, and Precincts
Artificial Neural Networks, Machine Learning, Deep Thinking Course
The trainers knowledge of the topics he was teaching.
Premier Partnership
Python for Advanced Machine Learning Course
Having access to the notebooks to work through
Premier Partnership
Python for Advanced Machine Learning Course
lots of information, all questions ansered, interesting examples
A1 Telekom Austria AG
Deep Learning for Telecom (with Python) Course
The informal exchanges we had during the lectures really helped me deepen my understanding of the subject
- Explore
Deep Reinforcement Learning with Python Course
In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.
Sacha Nandlall
Python for Advanced Machine Learning Course
Coverage and depth of topics
Anirban Basu
Machine Learning and Deep Learning Course
The training provided the right foundation that allows us to further to expand on, by showing how theory and practice go hand in hand. It actually got me more interested in the subject than I was before.
Jean-Paul van Tillo
Machine Learning and Deep Learning Course
We have gotten a lot more insight in to the subject matter. Some nice discussion were made with some real subjects within our company
Sebastiaan Holman
Machine Learning and Deep Learning Course
Doing exercises on real examples using Keras. Mihaly totally understood our expectations about this training.
Paul Kassis
Advanced Deep Learning Course
The exercises are sufficiently practical and do not need a high knowledge in Python to be done.
Alexandre GIRARD
Advanced Deep Learning Course
The global overview of deep learning
Bruno Charbonnier
Advanced Deep Learning Course
Topic. Very interesting!
Piotr
Introduction to Deep Learning Course
Trainers theoretical knowledge and willingness to solve the problems with the participants after the training
Grzegorz Mianowski
Introduction to Deep Learning Course
The topic is very interesting
Wojciech Baranowski
Introduction to Deep Learning Course
It was very interactive and more relaxed and informal than expected. We covered lots of topics in the time and the trainer was always receptive to talking more in detail or more generally about the topics and how they were related. I feel the training has given me the tools to continue learning as opposed to it being a one off session where learning stops once you've finished which is very important given the scale and complexity of the topic.
Jonathan Blease
Artificial Neural Networks, Machine Learning, Deep Thinking Course
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