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Scalable Machine Learning on Big Data using Apache Spark
by Romeo Kienzler- 3.8
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Approx. 7 hours to complete
This course will empower you with the skills to scale data science and machine learning (ML) tasks on Big Data sets using Apache Spark. NOTE: You will practice running machine learning tasks hands-on on an Apache Spark cluster provided by IBM at no charge during the course which you can continue to use afterwards....
Practical Machine Learning on H2O
by Darren Cook- 4.5
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Approx. 24 hours to complete
Even if you have no prior experience of machine learning, even if your math is weak, by the end of this course you will be able to make machine learning models using a variety of algorithms. We will be using linear models, random forest, GBMs and of course deep learning, as well as some unsupervised learning algorithms....
Perform better geotechnical numerical analysis
- 4.7
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The first course in the COGAN (Competency in Geotechnical Analysis) e-learning series There is also a worked example on deriving input parameters and interpreting output for structural elements in plane strain and axisymmetric models. On completing this course you will be able to prepare geotechnical numerical analyses more confidently, avoiding many of the common errors of novice users....
Sequences, Time Series and Prediction
by Laurence Moroney- 4.7
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Approx. 13 hours to complete
The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. Machine learning applied to time series Machine learning on time windows More on single layer neural network Adjusting the learning rate dynamically More on LSTM More info on Huber loss...
Digital transformation of megapolises: from zero to #1 in UN digital e-government ranking
by Artem Ermolaev , Andrey Belozerov- 4.3
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Approx. 18 hours to complete
This course will help you to navigate ambiguity in definitions of "Smart City". If you are already an expert in the field of Smart Cities, the course will give you the opportunity to assess your strengths and to improve knowledge in this field. Rules on the academic integrity in the course...
Fundamentals of Machine Learning for Healthcare
by Matthew LungrenTop Instructor , Serena YeungTop Instructor- 4.8
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Approx. 12 hours to complete
Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. This course will introduce the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. Why machine learning in healthcare? On Being Human in the Era of Clinical Machine Learning...
Laboratorio di programmazione: strumenti e programmi
by Marco Lapegna- 0.0
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10 Weeks
Impara a sviluppare dei programmi dinamici e interattivi usando il linguaggio Fortran e il linguaggio C. The second part of this course will mainly be based on practical activities and on an in-depth examination of the essential parts of this discipline. • Struttura e caratteristiche principali del sistema operativo Linux • Il linguaggio di programmazione FORTRAN e C...
$60
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Probabilistic Graphical Models 3: Learning
by Daphne Koller- 4.6
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Approx. 66 hours to complete
Following the first course, which focused on representation, and the second, which focused on inference, this course addresses the question of learning: how a PGM can be learned from a data set of examples. The course discusses the key problems of parameter estimation in both directed and undirected models, as well as the structure learning task for directed models....
Practical Reinforcement Learning
by Pavel Shvechikov , Alexander Panin- 4.3
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Approx. 26 hours to complete
Welcome to the Reinforcement Learning course. Reinforcement learning vs all More on approximate crossentropy method Rules on the academic integrity in the course Model-free reinforcement learning Supervised & Reinforcement Learning Combining supervised & reinforcement learning...
Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership
by Eric Siegel- 4.9
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Approx. 14 hours to complete
Machine learning runs the world. This course will guide you to lead or participate in the end-to-end implementation of machine learning (aka predictive analytics). Whether you'll participate on the business or tech side of a machine learning project, this course delivers essential, pertinent know-how. Course overview: Launching Machine Learning Sourcing the staff for a machine learning project...
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