Deep Learning Specialization
Every day 2.5 quintillion bytes of data are created and 90% of all the data in the world has been created in the last two years. Data Science & A.I. helps your business make smarter decisions. With that in mind, Anchormen is organizing value-packed trainings for your employees.
The Deep Learning specializations will teach your team the essentials as well as use real-life cases in order to help activate your data. Duration of the training is three days and takes place in one of our offices (Amsterdam, Groningen) or at your location.
The whole package costs a total of €1,995 per person and is coordinated for groups of 3-10 people.
The precise content of the training is decided based on a consultation with us. Every training is specially tailored based on the company’s needs and current level of subject matter understanding. Here are some of the topics you can expect to learn about:
- Some high-level background: why is Deep Learning suddenly becoming so powerful? What has changed? And what are (convolutional) neural networks?
- How to create (deep) neural networks using Keras.
- How to interpret output, how to debug, and how to use the results.
- How to unlock the potential of pretrained state-of-the-art networks by applying transfer learning.
- How to optimize (deep) neural networks.
- How to train a deep neural network using A.I. & Deep Learning GPU Platform.
- Recurrent Neural Networks.
Some form of familiarity with Machine Learning and some basic knowledge of neural networks should already be reached by trainees so they are allowed to follow the modules.
Deep Learning at Scale
With a good, solid GPU, one can quickly iterate over deep learning networks, and run experiments in days instead of months, hours instead of days, minutes instead of hours.Deep learning is a field with intense computational requirements and the choice of your GPU will fundamentally determine your deep learning experience. With no GPU this might look like months of waiting for an experiment to finish, or running an experiment for a day or more only to see that the chosen parameters were off.
Artificial intelligence is the use of computers to simulate human intelligence. Learning from data — a computer’s version of life experience — is how AI evolves. GPU deep learning is a new computing model in which deep neural networks are trained to recognize patterns from massive amounts of data. This new model has set off a string of “superhuman” achievements in image and speech recognition and sparked the era of AI computing.
Today’s advanced deep neural networks use algorithms, big data, and the computational power of the GPU to change this dynamic. Machines are now able to learn at a speed, accuracy, and scale that are driving true artificial intelligence and AI Computing.
Anchormen delivers high-performance multi-GPU acceleration and industry-vetted deep learning algorithms to dive into neural networks with the best in class deep learning experts from Anchormen’s team.
The real-world problems we handle are taken from Computer Vision, since Deep Learning shows exceptional performance in this discipline. Furthermore, the specialization emphasizes on the practical challenges of training large neural networks on real-world problems. When we can, we step over mathematical difficulties, and show how to use high-level libraries.
Python will be the core programming language for assignments, where we rely on the Keras library (backed by either Tensorflow or Theano) to train neural networks. If your graphical card allows it, we use the CUDA library to speed up the computations by running them on the GPU.
Personal coaching is available for applying Deep Learning to other problems, for instance in the realm of Natural Language Processing or Robotics. Moreover, an in-depth treatment of the mathematical foundations of (optimizations in) neural networks belongs to the possibilities, although a warning is in place: the theoretical foundation of many Deep Learning steps are rather shaky, even though they have proven to work well in practice.
Are you interested in this training?
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