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Course Outline
Introduction
- Overview of Machine Learning (ML) and Deep Learning (DL) concepts for government
- Future industry evolutions with ML and DL for government
Business Strategy with Deep Learning
- Defining business problems for government operations
- Data-driven decision making in the public sector
- Analytical thinking and mindset for government professionals
- Business strategy modeling for government initiatives
- Case studies and examples relevant to government agencies
Deep Learning Software and Tools
- Fundamentals of Python and Pandas for government applications
- Open source DL tools (TensorFlow, CNTK, Torch, Keras, etc.) for government use
- Use cases and examples in public sector operations
Deep Learning with Neural Networks
- Neural Network Learning (Backpropagation) for government projects
- Convolutional Neural Network (CNN) applications in the public sector
- Recurrent Neural Network (RNN) use cases for government agencies
- DL modeling examples relevant to government operations
Summary and Next Steps
Requirements
- An understanding of machine learning concepts for government applications
- Python programming experience
Audience
- Business analysts
- Data scientists
- Developers
14 Hours
Testimonials (2)
Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject
Ali Kattan - TWPI
Course - Natural Language Processing with TensorFlow
Very updated approach or CPI (tensor flow, era, learn) to do machine learning.
