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Course Outline
Introduction
TensorFlow Overview
- What is TensorFlow?
- TensorFlow features
What is AI
- Computational Psychology
- Computational Philosophy
Machine Learning
- Computational learning theory
- Computer algorithms for computational experience
Deep Learning
- Artificial neural networks
- Deep learning vs. machine learning
Preparing the Development Environment
- Installing and configuring TensorFlow
TensorFlow Quick Start
- Working with nodes
- Using the Keras API
Fraud Detection
- Reading and writing to data
- Preparing features
- Labeling data
- Normalizing data
- Splitting data into test data and training data
- Formatting input images
Predictions and Regressions
- Loading a model
- Visualizing predictions
- Creating regressions
Classifications
- Building and compiling a classifier model
- Training and testing the model
Summary and Conclusion
Requirements
- Python programming experience
Audience
- Data Scientists
14 Hours
Testimonials (5)
Examples/exercices perfectly adapted to our domain
Luc - CS Group
Course - Scaling Data Analysis with Python and Dask
The trainer was very available to answer all te kind of question I did
Caterina - Stamtech
Course - Developing APIs with Python and FastAPI
Transfer of practical knowledge and experience of the trainer.
Rumel Mateusz - Pojazdy Szynowe PESA Bydgoszcz SA
Machine Translated
It was a though course as we had to cover a lot in a short time frame. Our trainer knew a lot about the subject and delivered the content to address our requirements. It was lots of content to learn but our trainer was helpful and encouraging. He answered all our questions with good detail and we feel that we learned a lot. Exercises were well prepared and tasks were tailored accordingly to our needs. I enjoyed this course
Bozena Stansfield - New College Durham
Course - Build REST APIs with Python and Flask
As I was the only participant the training could be adapted to my needs.
