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Course Outline
- Overview of neural networks and deep learning
- The concept of Machine Learning (ML)
- Why we need neural networks and deep learning?
- Selecting networks for different problems and data types
- Learning and validating neural networks
- Comparing logistic regression to neural networks
- Neural Networks
- Biological inspirations for neural networks
- Neural Networks – Neurons, Perceptrons, and MLP (Multilayer Perceptron model)
- Learning MLP – the backpropagation algorithm
- Activation functions – linear, sigmoid, Tanh, Softmax
- Loss functions appropriate for forecasting and classification
- Parameters – learning rate, regularization, momentum
- Building Neural Networks in Python
- Evaluating performance of neural networks in Python
- Basics of Deep Networks
- What is deep learning?
- Architecture of Deep Networks – Parameters, Layers, Activation Functions, Loss Functions, Solvers
- Restricted Boltzmann Machines (RBMs)
- Autoencoders
- Deep Network Architectures
- Deep Belief Networks (DBN) – architecture, application
- Autoencoders
- Restricted Boltzmann Machines
- Convolutional Neural Networks
- Recursive Neural Networks
- Recurrent Neural Networks
- Overview of libraries and interfaces available in Python
- Caffe
- Theano
- TensorFlow
- Keras
- MXNet
- Choosing the appropriate library for the problem
- Building Deep Networks in Python
- Choosing the appropriate architecture for a given problem
- Hybrid deep networks
- Learning networks – selecting the appropriate library, architecture definition
- Tuning networks – initialization, activation functions, loss functions, optimization method
- Avoiding overfitting – detecting overfitting problems in deep networks, regularization
- Evaluating deep networks
- Case Studies in Python
- Image recognition – CNN
- Detecting anomalies with Autoencoders
- Forecasting time series with RNN
- Dimensionality reduction with Autoencoders
- Classification with RBM
Requirements
Familiarity or appreciation of machine learning, system architecture, and programming languages is desirable.
14 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 2600 € + VAT*
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Testimonials (1)
The training was organized and well-planned out, and I come out of it with systematized knowledge and a good look at topics we looked at
