28 hours (usually 4 days including breaks)
Background in physics, mathematics and programming. Involvment in image processing activities.
This course will give you knowledge in neural networks and generally in machine learning algorithm, deep learning (algorithms and applications).
This training is more focus on fundamentals, but will help you to choose the right technology : TensorFlow, Caffe, Teano, DeepDrive, Keras, etc. The examples are made in TensorFlow.
- 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
- Inputs and Placeholders
- Build the GraphS
- Train the Model
- The Graph
- The Session
- Train Loop
- Evaluate the Model
- Build the Eval Graph
- Eval Output
- Activation functions
- The perceptron learning algorithm
- Binary classification with the perceptron
- Document classification with the perceptron
- Limitations of the perceptron
From the Perceptron to 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
- Model Architecture
- Code Organization
- Launching and Training the Model
- Evaluating a Model
I generally enjoyed the knowledgeable trainer.
I was amazed at the standard of this class - I would say that it was university standard.
Very good all round overview. Good background into why Tensorflow operates as it does.
I liked the opportunities to ask questions and get more in depth explanations of the theory.
Given outlook of the technology: what technology/process might become more important in the future; see, what the technology can be used for.
I was benefit from topic selection. Style of training. Practice orientation.
I really appreciated the crystal clear answers of Chris to our questions.