Machine Learning is the science of programming computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.
At the heart of machine learning is the algorithm. A machine learning algorithm is an algorithm that is able to learn from data.
There are many different types of machine learning algorithms, with hundreds published each day, and they’re typically grouped by either learning style (i.e., supervised learning, unsupervised learning, semi-supervised learning) or by similarity in form or function (i.e., classification, regression, decision tree, clustering, deep learning, etc.).
All combinations of machine learning algorithms consist of the following:
- Representation:A set of classifiers or the language that a computer understands.
- Evaluation:Aka objective/scoring function.
- Optimization:Search method; often the highest-scoring classifier, for example; there are both off-the-shelf and custom optimization methods used.
Programming machines to learn requires a specific kind of approach. And there are many, from using basic decision trees to clustering to layers or artificial neural networks depending on what task you’re trying to accomplish and the type and amount of data that you have available.
One extremely important point is that machine learning is not just about automation. Machines can also provide valuable insights such as helping organizations rethink entire business models.
With all their processing power, Machines that learn are able to more quickly highlight or find patterns in big (or other) data that would have otherwise been missed by human beings.
Machine learning should be looked at as a tool that can be used to enhance humans’ abilities to solve problems and make informed inferences on a wide range of problems, from helping diagnose diseases to coming up with solutions for global climate change.
Machine Learning Courses
Tonex offers a 3-day Machine Learning Training Bootcamp technical training course covering the fundamentals of machine learning. Participants learn differences and similarities between Machine Learning, Artificial Intelligence, Deep Learning, Data Mining and Data Warehouse.
Who Should Attend
- Managers who need the vision and understanding of the many opportunities, costs, and likely performance hurdles in predictive modeling, especially as they pertain to large amounts of textual (or similar) data.
- Just about anyone whose work interfaces with data analysis who wants to learn key concepts, formulations, algorithms, and practical examples of what is possible in Machine Learning and Artificial Intelligence.
–Presenting highly customized learning solutions is what we do. For over 30 years Tonex has worked with organizations in improving their understanding and capabilities in topics often with new development, design, optimization, regulations and compliances that, frankly, can be difficult to comprehend.
–Ratings tabulated from student feedback post-course evaluations show an amazing 98 percent satisfaction score.
–Reasonably priced classes taught by the best trainers is the reason all kinds of organizations from Fortune 500 companies to government’s most important agencies return for updates in courses and hands-on workshops
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