Machine Learning from Data Preparation to Deep Learning (original) (raw)

This course is run in German as well: Maschinelles Lernen von der Datenaufbereitung bis zum Deep Learning


"Much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type — quietly but meaningfully improving core operations.", Jeff Bezos

© Bernd Klein

"Everything that civilisation has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools that AI may provide, but the eradication of war, disease, and poverty would be high on anyone’s list. Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last.", Stephen Hawking


All our courses are made-to-measure your expectations and are conveniently scheduled and delivered at various locations: Lake Constance or Berlin in Germany, Toronto in Canada. London in England. On-site training at the location of your choice is no problem. We offer in-house training courses all over Canada and Europe, especially in Germany, Switzerland, Austria, Luxembourg, Italy, the Netherlands and England and the UK. Covering cities like Munich, Stuttgart, Frankfurt, Saarbrücken, Zürich, Bern, Basel, Luzern, Bregenz, Strasbourg, Paris, Rhome, Amsterdam, London, and Toronto in Canada.

This course has been held as an online training course since March 2020. Further Information!

This intensive course is an excellent introduction to machine learning. It covers in detail the different sub-areas of machine learning, supervised learning, unsupervised learning and reinforcement learning. Each method is explained from the ground up using simple examples that are essential for understanding the process at hand and only require knowledge of basic Python. Then the methods are worked on in a contemporary way with the (auxiliary) modules NumPy, pandas, Matplotlib and the ML library sklearn. By optimizing the examples, the participant learns the importance of hyperparameters and combined approaches of ML using ensemble learning as an example.

Target Group:
Participants should have some general programming experience, preferably with a basic knowledge of Python. Prior knowledge of Python subtleties, machine learning, or data science is not required.

Content:

Lecturer: Philip Klein, Dr. Konrad Wienands

Dates:

Duration of the course:
5 days

The fees for this ML course per day:

ONLINE:

€449 per day (exclusive of VAT)

Toronto, Canada:

$633 per day (exclusive of HST)

Lake Constance, Hemmenhofen, Germany:

€449 per day (exclusive of VAT)
plus € 139 for full board and lodging in 4 star hotel

Hamburg, Munich, Frankfurt, Berlin (Germany):

€482 per day (exclusive of VAT)

Zurich and Geneva (Switzerland):

£482 per day (exclusive of VAT)

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