Highlights
- Explore TensorFlow Basics
- Create and initialise variables and data
- Use TensorFlow Mechanics to build graphs and train the model
- Gain knowledge about the perceptron learning algorithm and binary classification
- Support vector machines: kernels and margin classification
- Acquire knowledge in feedforward and feedback Artificial Neural Networks
- Learn Convolutional Neural Networks: explore model architecture and training
Course Details
Tensorflow Basics
- Creation, Initializing, Saving and Restoring TensorFlow variables
- Feeding, Reading and Preloading TensorFlow data
- How to use TensorFlow infrastructure to train models at scale
- Visualizing and Evaluating models with TensorBoard
TensorFlow Mechanics
- Inputs and Placeholders
- Build the Graph
- Inference
- Loss
- Training
- Train the model
- The graph
- The session
- Train loop
- Evaluate the model.
- Build the eval graph
- Eval output
The perceptron
- Activation functions
- The perceptron learning algorithm
- Binary classification with the perceptron
- Document classification with the perceptron
- Limitations of the perceptron
Support Vector Machines
- Kernels and the kernel trick.
- Maximum margin classification and support vectors
Artificial Neural Networks
- Nonlinear decision boundaries
- Feedforward and feedback artificial neural networks
- Multilayer perceptrons
- Minimizing the cost function
- Forward propagation
- Back propagation
- Improving the way neural networks learn
Convolutional Neural Networks
- Goals
- Model architecture
- Principles
- Code organization
- Launching and training the model.
- Evaluating a model.
Who should attend
The course is aimed at delegates with a Mathematical and/or Data Science/ML background.
Good programming knowledge, especially using the Python programming language.
Some experience and familiarity with the Pandas, Numpy and MatPlotLib python libraries for data analysis.
Feedback
4.8 out of 5 average
"There was lots of in depth content on how to maximise the use of the software library for our business and an excellent, helpful trainer to guide us."
JP, Software Engineer, TensorFlow, April 2021
“JBI did a great job of customizing their syllabus to suit our business needs and also bringing our team up to speed on the current best practices. Our teams varied widely in terms of experience and the Instructor handled this particularly well - very impressive”
Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022